diff --git a/community-plugins/.dockerignore b/community-plugins/.dockerignore
new file mode 100644
index 0000000..c08e9b0
--- /dev/null
+++ b/community-plugins/.dockerignore
@@ -0,0 +1,2 @@
+.*
+data
\ No newline at end of file
diff --git a/community-plugins/.gitignore b/community-plugins/.gitignore
new file mode 100644
index 0000000..108d10f
--- /dev/null
+++ b/community-plugins/.gitignore
@@ -0,0 +1,65 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*,cover
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+.*
+*.pyc
+**/__pycache__
+*/wordnet1.6
+*/Corpus
+*/a-hierarchy.xml
+*/a-synsets.xml
+*/wn16.txt
\ No newline at end of file
diff --git a/community-plugins/.gitlab-ci.yml b/community-plugins/.gitlab-ci.yml
new file mode 100644
index 0000000..f4464d8
--- /dev/null
+++ b/community-plugins/.gitlab-ci.yml
@@ -0,0 +1,51 @@
+# Uncomment if you want to use docker-in-docker
+# image: gsiupm/dockermake:latest
+# services:
+# - docker:dind
+# When using dind, it's wise to use the overlayfs driver for
+# improved performance.
+
+variables:
+  GIT_SUBMODULE_STRATEGY: recursive
+
+stages:
+  - build
+  - test
+  - push
+  - deploy
+  - clean
+
+before_script:
+  - make -e login
+
+build:
+  stage: build
+  script:
+    - make -e docker-build
+  only:
+    - master
+    - fix-makefiles
+
+test:
+  stage: test
+  script:
+    - make -e test
+
+push:
+  stage: push
+  script:
+    - make -e docker-push
+
+deploy:
+  stage: deploy
+  script:
+    - make -e deploy
+  only:
+    - master
+    - fix-makefiles
+
+clean :
+  stage: clean
+  script:
+    - make -e clean
+  when: manual
diff --git a/community-plugins/.gitmodules b/community-plugins/.gitmodules
new file mode 100644
index 0000000..4346aa5
--- /dev/null
+++ b/community-plugins/.gitmodules
@@ -0,0 +1,3 @@
+[submodule "data"]
+	path = data
+	url = ../data
diff --git a/community-plugins/.makefiles/README.md b/community-plugins/.makefiles/README.md
new file mode 100644
index 0000000..2ab487e
--- /dev/null
+++ b/community-plugins/.makefiles/README.md
@@ -0,0 +1,27 @@
+These makefiles are recipes for several common tasks in different types of projects.
+To add them to your project, simply do:
+
+```
+git remote add makefiles ssh://git@lab.cluster.gsi.dit.upm.es:2200/docs/templates/makefiles.git
+git subtree add --prefix=.makefiles/ makefiles master
+touch Makefile
+echo "include .makefiles/base.mk" >> Makefile
+```
+
+Now you can take advantage of the recipes.
+For instance, to add useful targets for a python project, just add this to your Makefile:
+
+```
+include .makefiles/python.mk
+```
+
+You may need to set special variables like the name of your project or the python versions you're targetting.
+Take a look at each specific `.mk` file for more information, and the `Makefile` in the [senpy](https://lab.cluster.gsi.dit.upm.es/senpy/senpy) project for a real use case.
+
+If you update the makefiles from your repository, make sure to push the changes for review in upstream (this repository):
+
+```
+make makefiles-push
+```
+
+It will automatically commit all unstaged changes in the .makefiles folder.
diff --git a/community-plugins/.makefiles/base.mk b/community-plugins/.makefiles/base.mk
new file mode 100644
index 0000000..4371ebe
--- /dev/null
+++ b/community-plugins/.makefiles/base.mk
@@ -0,0 +1,36 @@
+export
+NAME ?= $(shell basename $(CURDIR))
+VERSION ?= $(shell git describe --tags --dirty 2>/dev/null)
+
+ifeq ($(VERSION),)
+	VERSION:=unknown
+endif
+
+# Get the location of this makefile.
+MK_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
+
+-include .env
+-include ../.env
+
+help:           ## Show this help.
+	@fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/\(.*:\)[^#]*##\s*\(.*\)/\1\t\2/' | column -t -s "	"
+
+config:  ## Load config from the environment. You should run it once in every session before other tasks. Run: eval $(make config)
+	@awk '{ print "export " $$0}' ../.env
+	@awk '{ print "export " $$0}' .env
+	@echo "# Please, run: "
+	@echo "# eval \$$(make config)"
+# If you need to run a command on the key/value pairs, use this:
+# @awk '{ split($$0, a, "="); "echo " a[2] " | base64 -w 0" |& getline b64; print "export " a[1] "=" a[2]; print "export " a[1] "_BASE64=" b64}' .env
+
+ci:  ## Run a task using gitlab-runner. Only use to debug problems in the CI pipeline
+	gitlab-runner exec shell --builds-dir '.builds' --env CI_PROJECT_NAME=$(NAME) ${action}
+
+include $(MK_DIR)/makefiles.mk
+include $(MK_DIR)/docker.mk
+include $(MK_DIR)/git.mk
+
+info:: ## List all variables
+	env
+
+.PHONY:: config help ci
diff --git a/community-plugins/.makefiles/docker.mk b/community-plugins/.makefiles/docker.mk
new file mode 100644
index 0000000..33eb8b8
--- /dev/null
+++ b/community-plugins/.makefiles/docker.mk
@@ -0,0 +1,51 @@
+ifndef IMAGENAME
+	ifdef CI_REGISTRY_IMAGE
+		IMAGENAME=$(CI_REGISTRY_IMAGE)
+	else
+		IMAGENAME=$(NAME)
+	endif
+endif
+
+IMAGEWTAG?=$(IMAGENAME):$(VERSION)
+DOCKER_FLAGS?=$(-ti)
+DOCKER_CMD?=
+
+docker-login: ## Log in to the registry. It will only be used in the server, or when running a CI task locally (if CI_BUILD_TOKEN is set).
+ifeq ($(CI_BUILD_TOKEN),)
+	@echo "Not logging in to the docker registry" "$(CI_REGISTRY)"
+else
+	@docker login -u gitlab-ci-token -p $(CI_BUILD_TOKEN) $(CI_REGISTRY)
+endif
+ifeq ($(HUB_USER),)
+	@echo "Not logging in to global the docker registry"
+else
+	@docker login -u $(HUB_USER) -p $(HUB_PASSWORD)
+endif
+
+docker-clean: ## Remove docker credentials
+ifeq ($(HUB_USER),)
+else
+	@docker logout
+endif
+
+docker-run: ## Build a generic docker image
+	docker run $(DOCKER_FLAGS) $(IMAGEWTAG) $(DOCKER_CMD)
+
+docker-build: ## Build a generic docker image
+	docker build . -t $(IMAGEWTAG)
+
+docker-push: docker-build docker-login ## Push a generic docker image
+	docker push $(IMAGEWTAG)
+
+docker-latest-push: docker-build ## Push the latest image
+	docker tag $(IMAGEWTAG) $(IMAGENAME)
+	docker push $(IMAGENAME)
+
+login:: docker-login
+
+clean:: docker-clean
+
+docker-info:
+	@echo IMAGEWTAG=${IMAGEWTAG}
+
+.PHONY:: docker-login docker-clean login clean
diff --git a/community-plugins/.makefiles/git.mk b/community-plugins/.makefiles/git.mk
new file mode 100644
index 0000000..ac5eaad
--- /dev/null
+++ b/community-plugins/.makefiles/git.mk
@@ -0,0 +1,28 @@
+commit:
+	git commit -a
+
+tag:
+	git tag ${VERSION}
+
+git-push::
+	git push --tags -u origin HEAD
+
+git-pull:
+	git pull --all
+
+push-github: ## Push the code to github. You need to set up GITHUB_DEPLOY_KEY
+ifeq ($(GITHUB_DEPLOY_KEY),)
+else
+	$(eval KEY_FILE := "$(shell mktemp)")
+	@printf '%b' '$(GITHUB_DEPLOY_KEY)' > $(KEY_FILE)
+	@git remote rm github-deploy || true
+	git remote add github-deploy $(GITHUB_REPO)
+	-@GIT_SSH_COMMAND="ssh -i $(KEY_FILE)" git fetch github-deploy $(CI_COMMIT_REF_NAME)
+	@GIT_SSH_COMMAND="ssh -i $(KEY_FILE)" git push github-deploy HEAD:$(CI_COMMIT_REF_NAME)
+	rm $(KEY_FILE)
+endif
+
+push:: git-push
+pull:: git-pull
+
+.PHONY:: commit tag push git-push git-pull push-github 
diff --git a/community-plugins/.makefiles/k8s.mk b/community-plugins/.makefiles/k8s.mk
new file mode 100644
index 0000000..4c6f760
--- /dev/null
+++ b/community-plugins/.makefiles/k8s.mk
@@ -0,0 +1,51 @@
+# Deployment with Kubernetes
+
+# KUBE_CA_PEM_FILE is the path of a certificate file. It automatically set by GitLab
+# if you enable Kubernetes integration in a project.
+#
+# As of this writing, Kubernetes integration can not be set on a group level, so it has to
+# be manually set in every project.
+# Alternatively, we use a custom KUBE_CA_BUNDLE environment variable, which can be set at
+# the group level. In this case, the variable contains the whole content of the certificate,
+# which we dump to a temporary file
+#
+# Check if the KUBE_CA_PEM_FILE exists. Otherwise, create it from KUBE_CA_BUNDLE
+KUBE_CA_TEMP=false
+ifndef KUBE_CA_PEM_FILE
+KUBE_CA_PEM_FILE:=$$PWD/.ca.crt
+CREATED:=$(shell printf '%b\n' '$(KUBE_CA_BUNDLE)' > $(KUBE_CA_PEM_FILE))
+endif 
+KUBE_TOKEN?=""
+KUBE_NAMESPACE?=$(NAME)
+KUBECTL=docker run --rm -v $(KUBE_CA_PEM_FILE):/tmp/ca.pem -i lachlanevenson/k8s-kubectl --server="$(KUBE_URL)" --token="$(KUBE_TOKEN)" --certificate-authority="/tmp/ca.pem" -n $(KUBE_NAMESPACE)
+CI_COMMIT_REF_NAME?=master
+
+info:: ## Print variables. Useful for debugging.
+	@echo "#KUBERNETES"
+	@echo KUBE_URL=$(KUBE_URL)
+	@echo KUBE_CA_PEM_FILE=$(KUBE_CA_PEM_FILE)
+	@echo KUBE_CA_BUNDLE=$$KUBE_CA_BUNDLE
+	@echo KUBE_TOKEN=$(KUBE_TOKEN)
+	@echo KUBE_NAMESPACE=$(KUBE_NAMESPACE)
+	@echo KUBECTL=$(KUBECTL)
+
+	@echo "#CI"
+	@echo CI_PROJECT_NAME=$(CI_PROJECT_NAME)
+	@echo CI_REGISTRY=$(CI_REGISTRY)
+	@echo CI_REGISTRY_USER=$(CI_REGISTRY_USER)
+	@echo CI_COMMIT_REF_NAME=$(CI_COMMIT_REF_NAME)
+	@echo "CREATED=$(CREATED)"
+
+#
+# Deployment and advanced features
+# 
+
+
+deploy: ## Deploy to kubernetes using the credentials in KUBE_CA_PEM_FILE (or KUBE_CA_BUNDLE ) and TOKEN
+	@ls k8s/*.yaml k8s/*.yml k8s/*.tmpl 2>/dev/null || true
+	@cat k8s/*.yaml k8s/*.yml k8s/*.tmpl 2>/dev/null | envsubst | $(KUBECTL) apply -f -
+
+deploy-check: ## Get the deployed configuration.
+	@$(KUBECTL) get deploy,pods,svc,ingress
+
+.PHONY:: info deploy deploy-check
diff --git a/community-plugins/.makefiles/makefiles.mk b/community-plugins/.makefiles/makefiles.mk
new file mode 100644
index 0000000..03dcc17
--- /dev/null
+++ b/community-plugins/.makefiles/makefiles.mk
@@ -0,0 +1,17 @@
+makefiles-remote:
+	@git remote add makefiles ssh://git@lab.cluster.gsi.dit.upm.es:2200/docs/templates/makefiles.git 2>/dev/null || true
+
+makefiles-commit: makefiles-remote
+	git add -f .makefiles
+	git commit -em "Updated makefiles from ${NAME}"
+
+makefiles-push:
+	git subtree push --prefix=.makefiles/ makefiles $(NAME)
+
+makefiles-pull: makefiles-remote
+	git subtree pull --prefix=.makefiles/ makefiles master --squash
+
+pull:: makefiles-pull
+push:: makefiles-push
+
+.PHONY:: makefiles-remote makefiles-commit makefiles-push makefiles-pull pull push
diff --git a/community-plugins/.makefiles/precommit.mk b/community-plugins/.makefiles/precommit.mk
new file mode 100644
index 0000000..82fe75f
--- /dev/null
+++ b/community-plugins/.makefiles/precommit.mk
@@ -0,0 +1,5 @@
+init: ## Init pre-commit hooks (i.e. enforcing format checking before allowing a commit)
+	pip install --user pre-commit
+	pre-commit install
+
+.PHONY:: init
diff --git a/community-plugins/.makefiles/python.mk b/community-plugins/.makefiles/python.mk
new file mode 100644
index 0000000..2ad9559
--- /dev/null
+++ b/community-plugins/.makefiles/python.mk
@@ -0,0 +1,100 @@
+PYVERSIONS ?= 3.5
+PYMAIN ?= $(firstword $(PYVERSIONS))
+TARNAME ?= $(NAME)-$(VERSION).tar.gz 
+VERSIONFILE ?= $(NAME)/VERSION
+
+DEVPORT ?= 6000
+
+
+.FORCE:
+
+version: .FORCE
+	@echo $(VERSION) > $(VERSIONFILE)
+	@echo $(VERSION)
+
+yapf: ## Format python code
+	yapf -i -r $(NAME)
+	yapf -i -r tests
+
+dockerfiles: $(addprefix Dockerfile-,$(PYVERSIONS)) ## Generate dockerfiles for each python version
+	@unlink Dockerfile >/dev/null
+	ln -s Dockerfile-$(PYMAIN) Dockerfile
+
+Dockerfile-%: Dockerfile.template  ## Generate a specific dockerfile (e.g. Dockerfile-2.7)
+	sed "s/{{PYVERSION}}/$*/" Dockerfile.template > Dockerfile-$*
+
+quick_build: $(addprefix build-, $(PYMAIN))
+
+build: $(addprefix build-, $(PYVERSIONS)) ## Build all images / python versions
+
+build-%: version Dockerfile-%  ## Build a specific version (e.g. build-2.7)
+	docker build -t '$(IMAGEWTAG)-python$*' --cache-from $(IMAGENAME):python$* -f Dockerfile-$* .;
+
+dev-%: ## Launch a specific development environment using docker (e.g. dev-2.7)
+	@docker start $(NAME)-dev$* || (\
+		$(MAKE) build-$*; \
+		docker run -d -w /usr/src/app/ -p $(DEVPORT):5000 -v $$PWD:/usr/src/app --entrypoint=/bin/bash -ti --name $(NAME)-dev$* '$(IMAGEWTAG)-python$*'; \
+	)\
+
+	docker exec -ti $(NAME)-dev$* bash
+
+dev: dev-$(PYMAIN) ## Launch a development environment using docker, using the default python version
+
+quick_test: test-$(PYMAIN)
+
+test-%: ## Run setup.py from in an isolated container, built from the base image. (e.g. test-2.7)
+# This speeds tests up because the image has most (if not all) of the dependencies already.
+	docker rm $(NAME)-test-$* || true
+	docker create -ti --name $(NAME)-test-$* --entrypoint="" -w /usr/src/app/ $(IMAGENAME):python$* python setup.py test
+	docker cp . $(NAME)-test-$*:/usr/src/app
+	docker start -a $(NAME)-test-$*
+
+test: $(addprefix test-,$(PYVERSIONS)) ## Run the tests with the main python version
+
+run-%: build-%
+	docker run --rm -p $(DEVPORT):5000 -ti '$(IMAGEWTAG)-python$(PYMAIN)' --default-plugins
+
+run: run-$(PYMAIN)
+
+# Pypy - Upload a package
+
+dist/$(TARNAME): version
+	python setup.py sdist;
+
+sdist: dist/$(TARNAME) ## Generate the distribution file (wheel)
+
+pip_test-%: sdist ## Test the distribution file using pip install and a specific python version (e.g. pip_test-2.7)
+	docker run --rm -v $$PWD/dist:/dist/ python:$* pip install /dist/$(TARNAME);
+
+pip_test: $(addprefix pip_test-,$(PYVERSIONS)) ## Test pip installation with the main python version
+
+pip_upload: pip_test  ## Upload package to pip
+	python setup.py sdist upload ;
+
+# Pushing to docker
+
+push-latest: $(addprefix push-latest-,$(PYVERSIONS)) ## Push the "latest" tag to dockerhub
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGEWTAG)'
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGENAME)'
+	docker push '$(IMAGENAME):latest'
+	docker push '$(IMAGEWTAG)'
+
+push-latest-%: build-%  ## Push the latest image for a specific python version
+	docker tag $(IMAGENAME):$(VERSION)-python$* $(IMAGENAME):python$*
+	docker push $(IMAGENAME):$(VERSION)-python$*
+	docker push $(IMAGENAME):python$*
+
+push-%: build-%  ## Push the image of the current version (tagged). e.g. push-2.7
+	docker push $(IMAGENAME):$(VERSION)-python$*
+
+push:: $(addprefix push-,$(PYVERSIONS)) ## Push an image with the current version for every python version
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGEWTAG)'
+	docker push  $(IMAGENAME):$(VERSION)
+
+clean:: ## Clean older docker images and containers related to this project and dev environments
+	@docker stop $(addprefix $(NAME)-dev,$(PYVERSIONS)) 2>/dev/null || true
+	@docker rm $(addprefix $(NAME)-dev,$(PYVERSIONS)) 2>/dev/null || true
+	@docker ps -a | grep $(IMAGENAME) | awk '{ split($$2, vers, "-"); if(vers[0] != "${VERSION}"){ print $$1;}}' | xargs docker rm -v 2>/dev/null|| true
+	@docker images | grep $(IMAGENAME) | awk '{ split($$2, vers, "-"); if(vers[0] != "${VERSION}"){ print $$1":"$$2;}}' | xargs docker rmi 2>/dev/null|| true
+
+.PHONY:: yapf dockerfiles Dockerfile-% quick_build build build-% dev-% quick-dev test quick_test push-latest push-latest-% push-% push version .FORCE
diff --git a/community-plugins/.travis.yml b/community-plugins/.travis.yml
new file mode 100644
index 0000000..aabcb57
--- /dev/null
+++ b/community-plugins/.travis.yml
@@ -0,0 +1,12 @@
+language: python
+python:
+  - "2.7"
+  - "3.4"
+env:
+  - PLUGIN=example-plugin
+  - PLUGIN=sentiText
+install:
+  - "pip install senpy pytest"
+  - "python -m senpy --only-install -f $PLUGIN"
+script: 
+  - "py.test $PLUGIN"
\ No newline at end of file
diff --git a/community-plugins/Dockerfile b/community-plugins/Dockerfile
new file mode 100644
index 0000000..09c490c
--- /dev/null
+++ b/community-plugins/Dockerfile
@@ -0,0 +1 @@
+from gsiupm/senpy:1.0.1-python3.6
diff --git a/community-plugins/LICENSE b/community-plugins/LICENSE
new file mode 100644
index 0000000..8f71f43
--- /dev/null
+++ b/community-plugins/LICENSE
@@ -0,0 +1,202 @@
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+   1. Definitions.
+
+      "License" shall mean the terms and conditions for use, reproduction,
+      and distribution as defined by Sections 1 through 9 of this document.
+
+      "Licensor" shall mean the copyright owner or entity authorized by
+      the copyright owner that is granting the License.
+
+      "Legal Entity" shall mean the union of the acting entity and all
+      other entities that control, are controlled by, or are under common
+      control with that entity. For the purposes of this definition,
+      "control" means (i) the power, direct or indirect, to cause the
+      direction or management of such entity, whether by contract or
+      otherwise, or (ii) ownership of fifty percent (50%) or more of the
+      outstanding shares, or (iii) beneficial ownership of such entity.
+
+      "You" (or "Your") shall mean an individual or Legal Entity
+      exercising permissions granted by this License.
+
+      "Source" form shall mean the preferred form for making modifications,
+      including but not limited to software source code, documentation
+      source, and configuration files.
+
+      "Object" form shall mean any form resulting from mechanical
+      transformation or translation of a Source form, including but
+      not limited to compiled object code, generated documentation,
+      and conversions to other media types.
+
+      "Work" shall mean the work of authorship, whether in Source or
+      Object form, made available under the License, as indicated by a
+      copyright notice that is included in or attached to the work
+      (an example is provided in the Appendix below).
+
+      "Derivative Works" shall mean any work, whether in Source or Object
+      form, that is based on (or derived from) the Work and for which the
+      editorial revisions, annotations, elaborations, or other modifications
+      represent, as a whole, an original work of authorship. For the purposes
+      of this License, Derivative Works shall not include works that remain
+      separable from, or merely link (or bind by name) to the interfaces of,
+      the Work and Derivative Works thereof.
+
+      "Contribution" shall mean any work of authorship, including
+      the original version of the Work and any modifications or additions
+      to that Work or Derivative Works thereof, that is intentionally
+      submitted to Licensor for inclusion in the Work by the copyright owner
+      or by an individual or Legal Entity authorized to submit on behalf of
+      the copyright owner. For the purposes of this definition, "submitted"
+      means any form of electronic, verbal, or written communication sent
+      to the Licensor or its representatives, including but not limited to
+      communication on electronic mailing lists, source code control systems,
+      and issue tracking systems that are managed by, or on behalf of, the
+      Licensor for the purpose of discussing and improving the Work, but
+      excluding communication that is conspicuously marked or otherwise
+      designated in writing by the copyright owner as "Not a Contribution."
+
+      "Contributor" shall mean Licensor and any individual or Legal Entity
+      on behalf of whom a Contribution has been received by Licensor and
+      subsequently incorporated within the Work.
+
+   2. Grant of Copyright License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      copyright license to reproduce, prepare Derivative Works of,
+      publicly display, publicly perform, sublicense, and distribute the
+      Work and such Derivative Works in Source or Object form.
+
+   3. Grant of Patent License. Subject to the terms and conditions of
+      this License, each Contributor hereby grants to You a perpetual,
+      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
+      (except as stated in this section) patent license to make, have made,
+      use, offer to sell, sell, import, and otherwise transfer the Work,
+      where such license applies only to those patent claims licensable
+      by such Contributor that are necessarily infringed by their
+      Contribution(s) alone or by combination of their Contribution(s)
+      with the Work to which such Contribution(s) was submitted. If You
+      institute patent litigation against any entity (including a
+      cross-claim or counterclaim in a lawsuit) alleging that the Work
+      or a Contribution incorporated within the Work constitutes direct
+      or contributory patent infringement, then any patent licenses
+      granted to You under this License for that Work shall terminate
+      as of the date such litigation is filed.
+
+   4. Redistribution. You may reproduce and distribute copies of the
+      Work or Derivative Works thereof in any medium, with or without
+      modifications, and in Source or Object form, provided that You
+      meet the following conditions:
+
+      (a) You must give any other recipients of the Work or
+          Derivative Works a copy of this License; and
+
+      (b) You must cause any modified files to carry prominent notices
+          stating that You changed the files; and
+
+      (c) You must retain, in the Source form of any Derivative Works
+          that You distribute, all copyright, patent, trademark, and
+          attribution notices from the Source form of the Work,
+          excluding those notices that do not pertain to any part of
+          the Derivative Works; and
+
+      (d) If the Work includes a "NOTICE" text file as part of its
+          distribution, then any Derivative Works that You distribute must
+          include a readable copy of the attribution notices contained
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+          of the following places: within a NOTICE text file distributed
+          as part of the Derivative Works; within the Source form or
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+   Copyright {yyyy} {name of copyright owner}
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+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
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+       http://www.apache.org/licenses/LICENSE-2.0
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+   Unless required by applicable law or agreed to in writing, software
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+
diff --git a/community-plugins/Makefile b/community-plugins/Makefile
new file mode 100644
index 0000000..c6a4a7a
--- /dev/null
+++ b/community-plugins/Makefile
@@ -0,0 +1,30 @@
+PYVERSION=3.7
+NAME=senpycommunity
+REPO=gsiupm
+PLUGINS= $(filter %/, $(wildcard */))
+IMAGENAME=gsiupm/senpy-plugins-community
+DOCKER_FLAGS=-e MOCK_REQUESTS=$(MOCK_REQUESTS)
+DEV_PORT?=5000
+
+ifdef SENPY_FOLDER
+	DOCKER_FLAGS+= -v $(realpath $(SENPY_FOLDER)):/usr/src/app/
+	endif
+
+all: build run
+
+test-fast-%: docker-build
+	docker run $(DOCKER_FLAGS) -v $$PWD/$*:/senpy-plugins/ -v $$PWD/data:/data/ --rm $(IMAGEWTAG) --only-test $(TEST_FLAGS)
+
+test-fast: test-fast-/
+
+test: docker-build
+	docker run $(DOCKER_FLAGS) -v $$PWD/data:/data/ --rm $(IMAGEWTAG) --only-test $(TEST_FLAGS)
+
+dev: docker-build
+	docker run -p $(DEV_PORT):5000 $(DOCKER_FLAGS) -ti $(DOCKER_FLAGS) -v $$PWD/$*:/senpy-plugins/ --entrypoint /bin/bash -v $$PWD/data:/data/ --rm $(IMAGEWTAG)
+
+.PHONY:: test test-fast  dev
+
+include .makefiles/base.mk
+include .makefiles/k8s.mk
+
diff --git a/community-plugins/README.md b/community-plugins/README.md
new file mode 100644
index 0000000..3522327
--- /dev/null
+++ b/community-plugins/README.md
@@ -0,0 +1,76 @@
+# Senpy Plugins
+
+
+# Requirements
+
+Some of these plugins require licensed files to run, such as lexicons or corpora.
+You can **manually download these resources and add them to the `data` folder**.
+
+Most plugins will look for these resources on activation.
+By default, we set the flag `--allow-fail` in senpy, so if a plugin fails to activate, the server will still run with the remaining plugins.
+
+# Running
+
+## Using docker
+
+To deploy all the plugins in this repository, run:
+
+```
+docker-compose up
+```
+A server should now be available at `http://localhost:5000`.
+
+Alternatively, you can use docker manually with the version of senpy you wish:
+
+```
+docker run --rm -ti -p 5000:5000 -v $PWD:/senpy-plugins gsiupm/senpy:0.10.8-python2.7
+```
+
+Note that some versions are untested.
+
+## Manually
+
+First, install senpy from source or through pip:
+
+```
+pip install senpy
+```
+
+Now, you can try to run your plugins:
+
+```
+senpy -f .
+```
+
+Each plugin has different requirements.
+Senpy will try its best to automatically install requirements (python libraries and NLTK resources) for each plugin.
+Some cases may require manual installation of dependencies, or external packages.
+
+# For developers / Contributors
+
+## Licensed data
+
+In our deployments, we keep all licensed data in a private submodule.
+You will likely need to initialize this submodule if you're a contributor:
+
+```
+git submodule update --init --recursive 
+```
+
+## Adding a plugin from a separate repository
+
+To add a plugin that has been developed in its own repository, you can use git-subtree as so:
+
+```
+$mname=<your plugin name>
+$murl=<URL to your repository>
+
+git remote add $mname $murl
+git subtree add --prefix=$mname $mname master
+```
+
+Make sure to also add 
+
+# LICENSE
+
+This compilation of plugins for Senpy use Apache 2.0 License. Some of the resources used for train these plugins can not be distributed, specifically, resources for the plugins `emotion-anew` and `emotion-wnaffect`. For more information visit [Senpy documentation](senpy.readthedocs.io)
diff --git a/community-plugins/data b/community-plugins/data
new file mode 160000
index 0000000..f34155c
--- /dev/null
+++ b/community-plugins/data
@@ -0,0 +1 @@
+Subproject commit f34155c3891b8919a1d73bae410cb5113f1bf959
diff --git a/community-plugins/docker-compose.yml b/community-plugins/docker-compose.yml
new file mode 100644
index 0000000..3302ae5
--- /dev/null
+++ b/community-plugins/docker-compose.yml
@@ -0,0 +1,12 @@
+version: '3'
+services:
+  community:
+    build: .
+    image: "${IMAGEWTAG:-gsi-upm/senpy-community:dev}"
+    volumes:
+      - ".:/senpy-plugins/"
+      # - "./data:/data"
+    ports:
+      - '5000:5000'
+    command:
+      - "--allow-fail"
diff --git a/community-plugins/emotion-anew/README.md b/community-plugins/emotion-anew/README.md
new file mode 100755
index 0000000..3b47978
--- /dev/null
+++ b/community-plugins/emotion-anew/README.md
@@ -0,0 +1,60 @@
+# Plugin emotion-anew 
+
+This plugin consists on an **emotion classifier** that detects six possible emotions:
+- Anger : general-dislike.
+- Fear : negative-fear.
+- Disgust : shame.
+- Joy : gratitude, affective, enthusiasm, love, joy, liking.
+- Sadness : ingrattitude, daze, humlity, compassion, despair, anxiety, sadness.
+- Neutral: not detected a particulary emotion. 
+
+The plugin uses **ANEW lexicon** dictionary to calculate VAD (valence-arousal-dominance) of the sentence and determinate which emotion is closer to this value. To do this comparision, it is defined that each emotion has a centroid, calculated according to this article: http://www.aclweb.org/anthology/W10-0208. 
+
+The plugin is going to look for the words in the sentence that appear in the ANEW dictionary and calculate the average VAD score for the sentence. Once this score is calculated, it is going to seek the emotion that is closest to this value.
+
+The response of this plugin uses [Onyx ontology](https://www.gsi.dit.upm.es/ontologies/onyx/) developed at GSI UPM, to express the information.
+
+## Installation
+
+* Download
+```
+git clone https://lab.cluster.gsi.dit.upm.es/senpy/emotion-anew.git
+```
+* Get data
+```
+cd emotion-anew
+git submodule update --init --recursive
+```
+* Run
+```
+docker run -p 5000:5000 -v $PWD:/plugins gsiupm/senpy:python2.7 -f /plugins
+```
+
+## Data format
+
+`data/Corpus/affective-isear.tsv` contains data from ISEAR Databank: http://emotion-research.net/toolbox/toolboxdatabase.2006-10-13.2581092615 
+
+##Usage
+
+Params accepted:
+- Language: English (en) and Spanish (es).
+- Input: input text to analyse.
+
+
+Example request: 
+```
+http://senpy.cluster.gsi.dit.upm.es/api/?algo=emotion-anew&language=en&input=I%20love%20Madrid
+```
+
+Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section.
+# Known issues
+
+- To obtain Anew dictionary you can download from here: <https://github.com/hcorona/SMC2015/blob/master/resources/ANEW2010All.txt> 
+
+- This plugin only supports **Python2**
+
+
+![alt GSI Logo][logoGSI]
+
+[logoES]: https://www.gsi.dit.upm.es/ontologies/onyx/img/eurosentiment_logo.png "EuroSentiment logo"
+[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
diff --git a/community-plugins/emotion-anew/emotion-anew.py b/community-plugins/emotion-anew/emotion-anew.py
new file mode 100644
index 0000000..d40c83b
--- /dev/null
+++ b/community-plugins/emotion-anew/emotion-anew.py
@@ -0,0 +1,227 @@
+# -*- coding: utf-8 -*-
+
+import re
+import nltk
+import csv
+import sys
+import os
+import unicodedata
+import string
+import xml.etree.ElementTree as ET
+import math
+
+from sklearn.svm import LinearSVC
+from sklearn.feature_extraction import DictVectorizer
+
+from nltk import bigrams
+from nltk import trigrams
+from nltk.corpus import stopwords
+
+from pattern.en import parse as parse_en
+from pattern.es import parse as parse_es
+from senpy.plugins import EmotionPlugin, SenpyPlugin
+from senpy.models import Results, EmotionSet, Entry, Emotion
+
+
+class ANEW(EmotionPlugin):
+    description = "This plugin consists on an emotion classifier using ANEW lexicon dictionary. It averages the VAD (valence-arousal-dominance) value of each word in the text that is also in the ANEW dictionary. To obtain a categorical value (e.g., happy) use the emotion conversion API (e.g., `emotion-model=emoml:big6`)."
+    author = "@icorcuera"
+    version = "0.5.2"
+    name = "emotion-anew"
+
+    extra_params = {
+        "language": {
+            "description": "language of the input",
+            "aliases": ["language", "l"],
+            "required": True,
+            "options": ["es","en"],
+            "default": "en"
+        }
+    }
+
+    anew_path_es = "Dictionary/Redondo(2007).csv"
+    anew_path_en = "Dictionary/ANEW2010All.txt"
+    onyx__usesEmotionModel = "emoml:pad-dimensions"
+    nltk_resources = ['stopwords']
+
+    def activate(self, *args, **kwargs):
+        self._stopwords = stopwords.words('english')
+        dictionary={}
+        dictionary['es'] = {}
+        with self.open(self.anew_path_es,'r') as tabfile:
+            reader = csv.reader(tabfile, delimiter='\t')
+            for row in reader:
+                dictionary['es'][row[2]]={}
+                dictionary['es'][row[2]]['V']=row[3]
+                dictionary['es'][row[2]]['A']=row[5]
+                dictionary['es'][row[2]]['D']=row[7]
+        dictionary['en'] = {}
+        with self.open(self.anew_path_en,'r') as tabfile:
+            reader = csv.reader(tabfile, delimiter='\t')
+            for row in reader:
+                dictionary['en'][row[0]]={}
+                dictionary['en'][row[0]]['V']=row[2]
+                dictionary['en'][row[0]]['A']=row[4]
+                dictionary['en'][row[0]]['D']=row[6]
+        self._dictionary = dictionary
+
+    def _my_preprocessor(self, text):
+
+        regHttp = re.compile('(http://)[a-zA-Z0-9]*.[a-zA-Z0-9/]*(.[a-zA-Z0-9]*)?')
+        regHttps = re.compile('(https://)[a-zA-Z0-9]*.[a-zA-Z0-9/]*(.[a-zA-Z0-9]*)?')
+        regAt = re.compile('@([a-zA-Z0-9]*[*_/&%#@$]*)*[a-zA-Z0-9]*')
+        text = re.sub(regHttp, '', text)
+        text = re.sub(regAt, '', text)
+        text = re.sub('RT : ', '', text)
+        text = re.sub(regHttps, '', text)
+        text = re.sub('[0-9]', '', text)
+        text = self._delete_punctuation(text)
+        return text
+
+    def _delete_punctuation(self, text):
+
+        exclude = set(string.punctuation)
+        s = ''.join(ch for ch in text if ch not in exclude)
+        return s
+
+    def _extract_ngrams(self, text, lang):
+        unigrams_lemmas = []
+        unigrams_words = []
+        pos_tagged = []
+        if lang == 'es':
+            sentences = list(parse_es(text, lemmata=True).split())
+        else:
+            sentences = list(parse_en(text, lemmata=True).split())
+
+        for sentence in sentences:
+            for token in sentence:
+                if token[0].lower() not in self._stopwords:
+                    unigrams_words.append(token[0].lower())
+                    unigrams_lemmas.append(token[4])
+                    pos_tagged.append(token[1])
+
+        return unigrams_lemmas,unigrams_words,pos_tagged
+
+    def _find_ngrams(self, input_list, n):
+        return zip(*[input_list[i:] for i in range(n)])
+
+    def _extract_features(self, tweet,dictionary,lang):
+        feature_set={}
+        ngrams_lemmas,ngrams_words,pos_tagged = self._extract_ngrams(tweet,lang)
+        pos_tags={'NN':'NN', 'NNS':'NN', 'JJ':'JJ', 'JJR':'JJ', 'JJS':'JJ', 'RB':'RB', 'RBR':'RB',
+         'RBS':'RB', 'VB':'VB', 'VBD':'VB', 'VGB':'VB', 'VBN':'VB', 'VBP':'VB', 'VBZ':'VB'}
+        totalVAD=[0,0,0]
+        matches=0
+        for word in range(len(ngrams_lemmas)):
+            VAD=[]
+            if ngrams_lemmas[word] in dictionary:
+                matches+=1
+                totalVAD = [totalVAD[0]+float(dictionary[ngrams_lemmas[word]]['V']),
+                            totalVAD[1]+float(dictionary[ngrams_lemmas[word]]['A']),
+                            totalVAD[2]+float(dictionary[ngrams_lemmas[word]]['D'])]
+            elif ngrams_words[word] in dictionary:
+                matches+=1
+                totalVAD = [totalVAD[0]+float(dictionary[ngrams_words[word]]['V']),
+                            totalVAD[1]+float(dictionary[ngrams_words[word]]['A']),
+                            totalVAD[2]+float(dictionary[ngrams_words[word]]['D'])]
+        if matches==0:
+            emotion='neutral'
+        else:
+            totalVAD=[totalVAD[0]/matches,totalVAD[1]/matches,totalVAD[2]/matches]
+        feature_set['V'] = totalVAD[0]
+        feature_set['A'] = totalVAD[1]
+        feature_set['D'] = totalVAD[2]
+        return feature_set
+
+    def analyse_entry(self, entry, activity):
+        params = activity.params
+
+        text_input = entry.text
+
+        text = self._my_preprocessor(text_input)
+        dictionary = self._dictionary[params['language']]
+
+        feature_set=self._extract_features(text, dictionary, params['language'])
+
+        emotions = EmotionSet()
+        emotions.id = "Emotions0"
+
+        emotion1 = Emotion(id="Emotion0")
+        emotion1["emoml:pad-dimensions_pleasure"] = feature_set['V']
+        emotion1["emoml:pad-dimensions_arousal"] = feature_set['A']
+        emotion1["emoml:pad-dimensions_dominance"] = feature_set['D']
+
+        emotion1.prov(activity)
+        emotions.prov(activity)
+
+        emotions.onyx__hasEmotion.append(emotion1)
+        entry.emotions = [emotions, ]
+
+        yield entry
+
+    ontology = "http://gsi.dit.upm.es/ontologies/wnaffect/ns#"
+    test_cases = [
+        {
+            'name': 'anger with VAD=(2.12, 6.95, 5.05)',
+            'input': 'I hate you',
+            'expected': {
+                'onyx:hasEmotionSet': [{
+                    'onyx:hasEmotion': [{
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#arousal": 6.95,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#dominance": 5.05,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#valence": 2.12,
+                    }]
+                }]
+            }
+        }, {
+            'input': 'i am sad',
+            'expected': {
+                'onyx:hasEmotionSet': [{
+                    'onyx:hasEmotion': [{
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#arousal": 4.13,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#dominance": 3.45,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#valence": 1.61,
+
+                    }]
+                }]
+            }
+        }, {
+            'name': 'joy',
+            'input': 'i am happy with my marks',
+            'expected': {
+                'onyx:hasEmotionSet': [{
+                    'onyx:hasEmotion': [{
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#arousal": 6.49,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#dominance": 6.63,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#valence": 8.21,
+                    }]
+                }]
+            }
+        }, {
+            'name': 'negative-feat',
+            'input': 'This movie is scary',
+            'expected': {
+                'onyx:hasEmotionSet': [{
+                    'onyx:hasEmotion': [{
+                    "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#arousal": 5.8100000000000005,
+                    "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#dominance": 4.33,
+                    "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#valence": 5.050000000000001,
+
+                    }]
+                }]
+            }
+        }, {
+            'name': 'negative-fear',
+            'input': 'this cake is disgusting' ,
+            'expected': {
+                'onyx:hasEmotionSet': [{
+                    'onyx:hasEmotion': [{
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#arousal": 5.09,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#dominance": 4.4,
+                        "http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/anew/ns#valence": 5.109999999999999,
+
+                    }]
+                }]
+            }
+        }
+    ]
diff --git a/community-plugins/emotion-anew/emotion-anew.senpy b/community-plugins/emotion-anew/emotion-anew.senpy
new file mode 100644
index 0000000..4718fc6
--- /dev/null
+++ b/community-plugins/emotion-anew/emotion-anew.senpy
@@ -0,0 +1,11 @@
+---
+module: emotion-anew
+requirements:
+- numpy
+- pandas
+- nltk
+- scipy
+- scikit-learn
+- textblob
+- pattern
+- lxml
\ No newline at end of file
diff --git a/community-plugins/emotion-depechemood/depechemood_plugin.py b/community-plugins/emotion-depechemood/depechemood_plugin.py
new file mode 100644
index 0000000..d80e748
--- /dev/null
+++ b/community-plugins/emotion-depechemood/depechemood_plugin.py
@@ -0,0 +1,181 @@
+#!/usr/local/bin/python
+# coding: utf-8
+
+from future import standard_library
+standard_library.install_aliases()
+
+import os
+import re
+import sys
+import string
+import numpy as np
+from six.moves import urllib
+from nltk.corpus import stopwords
+
+from senpy import EmotionBox, models
+
+
+def ignore(dchars):
+    deletechars = "".join(dchars)
+    tbl = str.maketrans("", "", deletechars)
+    ignore = lambda s: s.translate(tbl)
+    return ignore
+
+
+class DepecheMood(EmotionBox):
+    '''
+    Plugin that uses the DepecheMood emotion lexicon.
+
+    DepecheMood is an emotion lexicon automatically generated from news articles where users expressed their associated emotions. It contains two languages (English and Italian), as well as three types of word representations (token, lemma and lemma#PoS). For English, the lexicon contains 165k tokens, while the Italian version contains 116k. Unsupervised techniques can be applied to generate simple but effective baselines. To learn more, please visit https://github.com/marcoguerini/DepecheMood and http://www.depechemood.eu/
+    '''
+
+    author = 'Oscar Araque'
+    name = 'emotion-depechemood'
+    version = '0.1'
+    requirements = ['pandas']
+    nltk_resources = ["stopwords"]
+
+    onyx__usesEmotionModel = 'wna:WNAModel'
+
+    EMOTIONS =  ['wna:negative-fear',
+                 'wna:amusement',
+                 'wna:anger',
+                 'wna:annoyance',
+                 'wna:indifference',
+                 'wna:joy',
+                 'wna:awe',
+                 'wna:sadness']
+
+    DM_EMOTIONS = ['AFRAID', 'AMUSED', 'ANGRY', 'ANNOYED', 'DONT_CARE', 'HAPPY', 'INSPIRED', 'SAD',]
+
+    def __init__(self, *args, **kwargs):
+        super(DepecheMood, self).__init__(*args, **kwargs)
+        self.LEXICON_URL = "https://github.com/marcoguerini/DepecheMood/raw/master/DepecheMood%2B%2B/DepecheMood_english_token_full.tsv"
+        self._denoise = ignore(set(string.punctuation)|set('«»'))
+        self._stop_words = []
+        self._lex_vocab = None
+        self._lex = None
+
+    def activate(self):
+        self._lex = self.download_lex()
+        self._lex_vocab = set(list(self._lex.keys()))
+        self._stop_words = stopwords.words('english') + ['']
+
+    def clean_str(self, string):
+        string = re.sub(r"[^A-Za-z0-9().,!?\'\`]", " ", string)
+        string = re.sub(r"[0-9]+", " num ", string)
+        string = re.sub(r"\'s", " \'s", string)
+        string = re.sub(r"\'ve", " \'ve", string)
+        string = re.sub(r"n\'t", " n\'t", string)
+        string = re.sub(r"\'re", " \'re", string)
+        string = re.sub(r"\'d", " \'d", string)
+        string = re.sub(r"\'ll", " \'ll", string)
+        string = re.sub(r"\.", " . ", string)
+        string = re.sub(r",", " , ", string)
+        string = re.sub(r"!", " ! ", string)
+        string = re.sub(r"\(", " ( ", string)
+        string = re.sub(r"\)", " ) ", string)
+        string = re.sub(r"\?", " ? ", string)
+        string = re.sub(r"\s{2,}", " ", string)
+        return string.strip().lower()
+
+    def preprocess(self, text):
+        if text is None:
+            return None
+        tokens = self._denoise(self.clean_str(text)).split(' ')
+        tokens = [tok for tok in tokens if tok not in self._stop_words]
+        return tokens   
+
+    def estimate_emotion(self, tokens, emotion):
+        s = []
+        for tok in tokens:
+            s.append(self._lex[tok][emotion])
+        dividend = np.sum(s) if np.sum(s) > 0 else 0
+        divisor = len(s) if len(s) > 0 else 1
+        S = np.sum(s) / divisor
+        return S
+
+    def estimate_all_emotions(self, tokens):
+        S = []
+        intersection = set(tokens) & self._lex_vocab
+        for emotion in self.DM_EMOTIONS:
+            s = self.estimate_emotion(intersection, emotion)
+            S.append(s)
+        return S
+
+    def download_lex(self, file_path='DepecheMood_english_token_full.tsv', freq_threshold=10):
+
+        import pandas as pd
+
+        try:
+            file_path = self.find_file(file_path)
+        except IOError:
+            file_path = self.path(file_path)
+            filename, _ = urllib.request.urlretrieve(self.LEXICON_URL, file_path)
+
+        lexicon = pd.read_csv(file_path, sep='\t', index_col=0)
+        lexicon = lexicon[lexicon['freq'] >= freq_threshold]
+        lexicon.drop('freq', axis=1, inplace=True)
+        lexicon = lexicon.T.to_dict()
+        return lexicon
+
+    def predict_one(self, features, **kwargs):
+        tokens = self.preprocess(features[0])
+        estimation = self.estimate_all_emotions(tokens)
+        return estimation
+
+    test_cases = [
+        {
+            'entry': {
+                'nif:isString': 'My cat is very happy',
+            },
+            'expected': {
+                'onyx:hasEmotionSet': [
+                    {
+                        'onyx:hasEmotion': [
+                            {
+                             'onyx:hasEmotionCategory': 'wna:negative-fear',
+                             'onyx:hasEmotionIntensity': 0.05278117640010922
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:amusement',
+                                'onyx:hasEmotionIntensity': 0.2114806151413433,
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:anger',
+                                'onyx:hasEmotionIntensity': 0.05726119426520887
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:annoyance',
+                                'onyx:hasEmotionIntensity': 0.12295990731053638,
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:indifference',
+                                'onyx:hasEmotionIntensity': 0.1860159893608025,
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:joy',
+                                'onyx:hasEmotionIntensity': 0.12904050973724163,
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:awe',
+                                'onyx:hasEmotionIntensity': 0.17973650399862967,
+                            },
+                            {
+                                'onyx:hasEmotionCategory': 'wna:sadness',
+                                'onyx:hasEmotionIntensity': 0.060724103786128455,
+                            },
+                        ]
+                    }
+                ]
+            }
+        }
+    ]
+
+
+if __name__ == '__main__':
+    from senpy.utils import easy, easy_load, easy_test
+    # sp, app = easy_load()
+    # for plug in sp.analysis_plugins:
+    #     plug.test()
+    easy_test(debug=False)
diff --git a/community-plugins/emotion-wnaffect/.gitignore b/community-plugins/emotion-wnaffect/.gitignore
new file mode 100644
index 0000000..8d35cb3
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.gitignore
@@ -0,0 +1,2 @@
+__pycache__
+*.pyc
diff --git a/community-plugins/emotion-wnaffect/.gitlab-ci.yml b/community-plugins/emotion-wnaffect/.gitlab-ci.yml
new file mode 100644
index 0000000..4806968
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.gitlab-ci.yml
@@ -0,0 +1,67 @@
+# Uncomment if you want to use docker-in-docker
+# image: gsiupm/dockermake:latest
+# services:
+# - docker:dind
+# When using dind, it's wise to use the overlayfs driver for
+# improved performance.
+
+stages:
+  - test
+  - push
+  - deploy
+  - clean
+
+before_script:
+  - make -e login
+
+.test: &test_definition
+  stage: test
+  script:
+    - make -e test-$PYTHON_VERSION
+
+test-3.5:
+  <<: *test_definition
+  variables:
+    PYTHON_VERSION: "3.5"
+
+.image: &image_definition
+  stage: push
+  script:
+    - make -e push-$PYTHON_VERSION
+  only:
+    - tags
+    - triggers
+
+push-3.5:
+  <<: *image_definition
+  variables:
+    PYTHON_VERSION: "3.5"
+
+push-latest:
+  <<: *image_definition
+  variables:
+    PYTHON_VERSION: latest
+  only:
+    - tags
+    - triggers
+
+deploy:
+  stage: deploy
+  environment: production
+  script:
+    - make -e deploy
+  only:
+    - tags
+    - triggers
+
+clean :
+  stage: clean
+  script:
+    - make -e clean
+  when: manual
+
+cleanup_py:
+   stage: clean
+   when: always   # this is important; run even if preceding stages failed.
+   script:
+    - docker logout
diff --git a/community-plugins/emotion-wnaffect/.makefiles/README.md b/community-plugins/emotion-wnaffect/.makefiles/README.md
new file mode 100644
index 0000000..2ab487e
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/README.md
@@ -0,0 +1,27 @@
+These makefiles are recipes for several common tasks in different types of projects.
+To add them to your project, simply do:
+
+```
+git remote add makefiles ssh://git@lab.cluster.gsi.dit.upm.es:2200/docs/templates/makefiles.git
+git subtree add --prefix=.makefiles/ makefiles master
+touch Makefile
+echo "include .makefiles/base.mk" >> Makefile
+```
+
+Now you can take advantage of the recipes.
+For instance, to add useful targets for a python project, just add this to your Makefile:
+
+```
+include .makefiles/python.mk
+```
+
+You may need to set special variables like the name of your project or the python versions you're targetting.
+Take a look at each specific `.mk` file for more information, and the `Makefile` in the [senpy](https://lab.cluster.gsi.dit.upm.es/senpy/senpy) project for a real use case.
+
+If you update the makefiles from your repository, make sure to push the changes for review in upstream (this repository):
+
+```
+make makefiles-push
+```
+
+It will automatically commit all unstaged changes in the .makefiles folder.
diff --git a/community-plugins/emotion-wnaffect/.makefiles/base.mk b/community-plugins/emotion-wnaffect/.makefiles/base.mk
new file mode 100644
index 0000000..4371ebe
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/base.mk
@@ -0,0 +1,36 @@
+export
+NAME ?= $(shell basename $(CURDIR))
+VERSION ?= $(shell git describe --tags --dirty 2>/dev/null)
+
+ifeq ($(VERSION),)
+	VERSION:=unknown
+endif
+
+# Get the location of this makefile.
+MK_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
+
+-include .env
+-include ../.env
+
+help:           ## Show this help.
+	@fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/\(.*:\)[^#]*##\s*\(.*\)/\1\t\2/' | column -t -s "	"
+
+config:  ## Load config from the environment. You should run it once in every session before other tasks. Run: eval $(make config)
+	@awk '{ print "export " $$0}' ../.env
+	@awk '{ print "export " $$0}' .env
+	@echo "# Please, run: "
+	@echo "# eval \$$(make config)"
+# If you need to run a command on the key/value pairs, use this:
+# @awk '{ split($$0, a, "="); "echo " a[2] " | base64 -w 0" |& getline b64; print "export " a[1] "=" a[2]; print "export " a[1] "_BASE64=" b64}' .env
+
+ci:  ## Run a task using gitlab-runner. Only use to debug problems in the CI pipeline
+	gitlab-runner exec shell --builds-dir '.builds' --env CI_PROJECT_NAME=$(NAME) ${action}
+
+include $(MK_DIR)/makefiles.mk
+include $(MK_DIR)/docker.mk
+include $(MK_DIR)/git.mk
+
+info:: ## List all variables
+	env
+
+.PHONY:: config help ci
diff --git a/community-plugins/emotion-wnaffect/.makefiles/docker.mk b/community-plugins/emotion-wnaffect/.makefiles/docker.mk
new file mode 100644
index 0000000..f74d93f
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/docker.mk
@@ -0,0 +1,29 @@
+IMAGENAME?=$(NAME)
+IMAGEWTAG?=$(IMAGENAME):$(VERSION)
+
+docker-login: ## Log in to the registry. It will only be used in the server, or when running a CI task locally (if CI_BUILD_TOKEN is set).
+ifeq ($(CI_BUILD_TOKEN),)
+	@echo "Not logging in to the docker registry" "$(CI_REGISTRY)"
+else
+	@docker login -u gitlab-ci-token -p $(CI_BUILD_TOKEN) $(CI_REGISTRY)
+endif
+ifeq ($(HUB_USER),)
+	@echo "Not logging in to global the docker registry"
+else
+	@docker login -u $(HUB_USER) -p $(HUB_PASSWORD)
+endif
+
+docker-clean: ## Remove docker credentials
+ifeq ($(HUB_USER),)
+else
+	@docker logout
+endif
+
+login:: docker-login
+
+clean:: docker-clean
+
+docker-info:
+	@echo IMAGEWTAG=${IMAGEWTAG}
+
+.PHONY:: docker-login docker-clean login clean
diff --git a/community-plugins/emotion-wnaffect/.makefiles/git.mk b/community-plugins/emotion-wnaffect/.makefiles/git.mk
new file mode 100644
index 0000000..836eb14
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/git.mk
@@ -0,0 +1,28 @@
+commit:
+	git commit -a
+
+tag:
+	git tag ${VERSION}
+
+git-push::
+	git push --tags -u origin HEAD
+
+git-pull:
+	git pull --all
+
+push-github: ## Push the code to github. You need to set up GITHUB_DEPLOY_KEY
+ifeq ($(GITHUB_DEPLOY_KEY),)
+else
+	$(eval KEY_FILE := "$(shell mktemp)")
+	@echo "$(GITHUB_DEPLOY_KEY)" > $(KEY_FILE)
+	@git remote rm github-deploy || true
+	git remote add github-deploy $(GITHUB_REPO)
+	-@GIT_SSH_COMMAND="ssh -i $(KEY_FILE)" git fetch github-deploy $(CI_COMMIT_REF_NAME)
+	@GIT_SSH_COMMAND="ssh -i $(KEY_FILE)" git push github-deploy HEAD:$(CI_COMMIT_REF_NAME)
+	rm $(KEY_FILE)
+endif
+
+push:: git-push
+pull:: git-pull
+
+.PHONY:: commit tag push git-push git-pull push-github 
diff --git a/community-plugins/emotion-wnaffect/.makefiles/k8s.mk b/community-plugins/emotion-wnaffect/.makefiles/k8s.mk
new file mode 100644
index 0000000..a493b4a
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/k8s.mk
@@ -0,0 +1,51 @@
+# Deployment with Kubernetes
+
+# KUBE_CA_PEM_FILE is the path of a certificate file. It automatically set by GitLab
+# if you enable Kubernetes integration in a project.
+#
+# As of this writing, Kubernetes integration can not be set on a group level, so it has to
+# be manually set in every project.
+# Alternatively, we use a custom KUBE_CA_BUNDLE environment variable, which can be set at
+# the group level. In this case, the variable contains the whole content of the certificate,
+# which we dump to a temporary file
+#
+# Check if the KUBE_CA_PEM_FILE exists. Otherwise, create it from KUBE_CA_BUNDLE
+KUBE_CA_TEMP=false
+ifndef KUBE_CA_PEM_FILE
+KUBE_CA_PEM_FILE:=$$PWD/.ca.crt
+CREATED:=$(shell echo -e "$(KUBE_CA_BUNDLE)" > $(KUBE_CA_PEM_FILE))
+endif 
+KUBE_TOKEN?=""
+KUBE_NAMESPACE?=$(NAME)
+KUBECTL=docker run --rm -v $(KUBE_CA_PEM_FILE):/tmp/ca.pem -i lachlanevenson/k8s-kubectl --server="$(KUBE_URL)" --token="$(KUBE_TOKEN)" --certificate-authority="/tmp/ca.pem" -n $(KUBE_NAMESPACE)
+CI_COMMIT_REF_NAME?=master
+
+info:: ## Print variables. Useful for debugging.
+	@echo "#KUBERNETES"
+	@echo KUBE_URL=$(KUBE_URL)
+	@echo KUBE_CA_PEM_FILE=$(KUBE_CA_PEM_FILE)
+	@echo KUBE_CA_BUNDLE=$$KUBE_CA_BUNDLE
+	@echo KUBE_TOKEN=$(KUBE_TOKEN)
+	@echo KUBE_NAMESPACE=$(KUBE_NAMESPACE)
+	@echo KUBECTL=$(KUBECTL)
+
+	@echo "#CI"
+	@echo CI_PROJECT_NAME=$(CI_PROJECT_NAME)
+	@echo CI_REGISTRY=$(CI_REGISTRY)
+	@echo CI_REGISTRY_USER=$(CI_REGISTRY_USER)
+	@echo CI_COMMIT_REF_NAME=$(CI_COMMIT_REF_NAME)
+	@echo "CREATED=$(CREATED)"
+
+#
+# Deployment and advanced features
+# 
+
+
+deploy: ## Deploy to kubernetes using the credentials in KUBE_CA_PEM_FILE (or KUBE_CA_BUNDLE ) and TOKEN
+	@ls k8s/*.yaml k8s/*.yml k8s/*.tmpl 2>/dev/null || true
+	@cat k8s/*.yaml k8s/*.yml k8s/*.tmpl 2>/dev/null | envsubst | $(KUBECTL) apply -f -
+
+deploy-check: ## Get the deployed configuration.
+	@$(KUBECTL) get deploy,pods,svc,ingress
+
+.PHONY:: info deploy deploy-check
diff --git a/community-plugins/emotion-wnaffect/.makefiles/makefiles.mk b/community-plugins/emotion-wnaffect/.makefiles/makefiles.mk
new file mode 100644
index 0000000..03dcc17
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/makefiles.mk
@@ -0,0 +1,17 @@
+makefiles-remote:
+	@git remote add makefiles ssh://git@lab.cluster.gsi.dit.upm.es:2200/docs/templates/makefiles.git 2>/dev/null || true
+
+makefiles-commit: makefiles-remote
+	git add -f .makefiles
+	git commit -em "Updated makefiles from ${NAME}"
+
+makefiles-push:
+	git subtree push --prefix=.makefiles/ makefiles $(NAME)
+
+makefiles-pull: makefiles-remote
+	git subtree pull --prefix=.makefiles/ makefiles master --squash
+
+pull:: makefiles-pull
+push:: makefiles-push
+
+.PHONY:: makefiles-remote makefiles-commit makefiles-push makefiles-pull pull push
diff --git a/community-plugins/emotion-wnaffect/.makefiles/precommit.mk b/community-plugins/emotion-wnaffect/.makefiles/precommit.mk
new file mode 100644
index 0000000..82fe75f
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/precommit.mk
@@ -0,0 +1,5 @@
+init: ## Init pre-commit hooks (i.e. enforcing format checking before allowing a commit)
+	pip install --user pre-commit
+	pre-commit install
+
+.PHONY:: init
diff --git a/community-plugins/emotion-wnaffect/.makefiles/python.mk b/community-plugins/emotion-wnaffect/.makefiles/python.mk
new file mode 100644
index 0000000..2ad9559
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/.makefiles/python.mk
@@ -0,0 +1,100 @@
+PYVERSIONS ?= 3.5
+PYMAIN ?= $(firstword $(PYVERSIONS))
+TARNAME ?= $(NAME)-$(VERSION).tar.gz 
+VERSIONFILE ?= $(NAME)/VERSION
+
+DEVPORT ?= 6000
+
+
+.FORCE:
+
+version: .FORCE
+	@echo $(VERSION) > $(VERSIONFILE)
+	@echo $(VERSION)
+
+yapf: ## Format python code
+	yapf -i -r $(NAME)
+	yapf -i -r tests
+
+dockerfiles: $(addprefix Dockerfile-,$(PYVERSIONS)) ## Generate dockerfiles for each python version
+	@unlink Dockerfile >/dev/null
+	ln -s Dockerfile-$(PYMAIN) Dockerfile
+
+Dockerfile-%: Dockerfile.template  ## Generate a specific dockerfile (e.g. Dockerfile-2.7)
+	sed "s/{{PYVERSION}}/$*/" Dockerfile.template > Dockerfile-$*
+
+quick_build: $(addprefix build-, $(PYMAIN))
+
+build: $(addprefix build-, $(PYVERSIONS)) ## Build all images / python versions
+
+build-%: version Dockerfile-%  ## Build a specific version (e.g. build-2.7)
+	docker build -t '$(IMAGEWTAG)-python$*' --cache-from $(IMAGENAME):python$* -f Dockerfile-$* .;
+
+dev-%: ## Launch a specific development environment using docker (e.g. dev-2.7)
+	@docker start $(NAME)-dev$* || (\
+		$(MAKE) build-$*; \
+		docker run -d -w /usr/src/app/ -p $(DEVPORT):5000 -v $$PWD:/usr/src/app --entrypoint=/bin/bash -ti --name $(NAME)-dev$* '$(IMAGEWTAG)-python$*'; \
+	)\
+
+	docker exec -ti $(NAME)-dev$* bash
+
+dev: dev-$(PYMAIN) ## Launch a development environment using docker, using the default python version
+
+quick_test: test-$(PYMAIN)
+
+test-%: ## Run setup.py from in an isolated container, built from the base image. (e.g. test-2.7)
+# This speeds tests up because the image has most (if not all) of the dependencies already.
+	docker rm $(NAME)-test-$* || true
+	docker create -ti --name $(NAME)-test-$* --entrypoint="" -w /usr/src/app/ $(IMAGENAME):python$* python setup.py test
+	docker cp . $(NAME)-test-$*:/usr/src/app
+	docker start -a $(NAME)-test-$*
+
+test: $(addprefix test-,$(PYVERSIONS)) ## Run the tests with the main python version
+
+run-%: build-%
+	docker run --rm -p $(DEVPORT):5000 -ti '$(IMAGEWTAG)-python$(PYMAIN)' --default-plugins
+
+run: run-$(PYMAIN)
+
+# Pypy - Upload a package
+
+dist/$(TARNAME): version
+	python setup.py sdist;
+
+sdist: dist/$(TARNAME) ## Generate the distribution file (wheel)
+
+pip_test-%: sdist ## Test the distribution file using pip install and a specific python version (e.g. pip_test-2.7)
+	docker run --rm -v $$PWD/dist:/dist/ python:$* pip install /dist/$(TARNAME);
+
+pip_test: $(addprefix pip_test-,$(PYVERSIONS)) ## Test pip installation with the main python version
+
+pip_upload: pip_test  ## Upload package to pip
+	python setup.py sdist upload ;
+
+# Pushing to docker
+
+push-latest: $(addprefix push-latest-,$(PYVERSIONS)) ## Push the "latest" tag to dockerhub
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGEWTAG)'
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGENAME)'
+	docker push '$(IMAGENAME):latest'
+	docker push '$(IMAGEWTAG)'
+
+push-latest-%: build-%  ## Push the latest image for a specific python version
+	docker tag $(IMAGENAME):$(VERSION)-python$* $(IMAGENAME):python$*
+	docker push $(IMAGENAME):$(VERSION)-python$*
+	docker push $(IMAGENAME):python$*
+
+push-%: build-%  ## Push the image of the current version (tagged). e.g. push-2.7
+	docker push $(IMAGENAME):$(VERSION)-python$*
+
+push:: $(addprefix push-,$(PYVERSIONS)) ## Push an image with the current version for every python version
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGEWTAG)'
+	docker push  $(IMAGENAME):$(VERSION)
+
+clean:: ## Clean older docker images and containers related to this project and dev environments
+	@docker stop $(addprefix $(NAME)-dev,$(PYVERSIONS)) 2>/dev/null || true
+	@docker rm $(addprefix $(NAME)-dev,$(PYVERSIONS)) 2>/dev/null || true
+	@docker ps -a | grep $(IMAGENAME) | awk '{ split($$2, vers, "-"); if(vers[0] != "${VERSION}"){ print $$1;}}' | xargs docker rm -v 2>/dev/null|| true
+	@docker images | grep $(IMAGENAME) | awk '{ split($$2, vers, "-"); if(vers[0] != "${VERSION}"){ print $$1":"$$2;}}' | xargs docker rmi 2>/dev/null|| true
+
+.PHONY:: yapf dockerfiles Dockerfile-% quick_build build build-% dev-% quick-dev test quick_test push-latest push-latest-% push-% push version .FORCE
diff --git a/community-plugins/emotion-wnaffect/Dockerfile-2.7 b/community-plugins/emotion-wnaffect/Dockerfile-2.7
new file mode 100644
index 0000000..4dce575
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/Dockerfile-2.7
@@ -0,0 +1,5 @@
+FROM gsiupm/senpy:python2.7
+
+MAINTAINER manuel.garcia-amado.sancho@alumnos.upm.es
+
+COPY data /data
diff --git a/community-plugins/emotion-wnaffect/Dockerfile-3.5 b/community-plugins/emotion-wnaffect/Dockerfile-3.5
new file mode 100644
index 0000000..cdc7061
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/Dockerfile-3.5
@@ -0,0 +1,4 @@
+FROM gsiupm/senpy:python3.5
+
+MAINTAINER manuel.garcia-amado.sancho@alumnos.upm.es
+COPY data /data
diff --git a/community-plugins/emotion-wnaffect/Dockerfile.template b/community-plugins/emotion-wnaffect/Dockerfile.template
new file mode 100644
index 0000000..27c30a5
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/Dockerfile.template
@@ -0,0 +1,3 @@
+FROM gsiupm/senpy:python{{PYVERSION}}
+
+MAINTAINER manuel.garcia-amado.sancho@alumnos.upm.es
diff --git a/community-plugins/emotion-wnaffect/Makefile b/community-plugins/emotion-wnaffect/Makefile
new file mode 100644
index 0000000..6308ecc
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/Makefile
@@ -0,0 +1,9 @@
+NAME:=wnaffect
+VERSIONFILE:=VERSION
+IMAGENAME:=registry.cluster.gsi.dit.upm.es/senpy/emotion-wnaffect
+PYVERSIONS:=2.7 3.5
+DEVPORT:=5000
+	
+include .makefiles/base.mk
+include .makefiles/k8s.mk
+include .makefiles/python.mk
diff --git a/community-plugins/emotion-wnaffect/README.md b/community-plugins/emotion-wnaffect/README.md
new file mode 100644
index 0000000..f4f5cfe
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/README.md
@@ -0,0 +1,62 @@
+# WordNet-Affect plugin
+
+This plugin uses WordNet-Affect (http://wndomains.fbk.eu/wnaffect.html) to calculate the percentage of each emotion. The plugin classifies among five diferent emotions: anger, fear, disgust, joy and sadness. It is has been used a emotion mapping enlarge the emotions:
+
+- anger : general-dislike
+- fear : negative-fear
+- disgust : shame
+- joy : gratitude, affective, enthusiasm, love, joy, liking
+- sadness : ingrattitude, daze, humlity, compassion, despair, anxiety, sadness
+
+## Installation
+
+* Download
+```
+git clone https://lab.cluster.gsi.dit.upm.es/senpy/emotion-wnaffect.git
+```
+* Get data
+```
+cd emotion-wnaffect
+git submodule update --init --recursive
+```
+* Run 
+```
+docker run -p 5000:5000 -v $PWD:/plugins gsiupm/senpy -f /plugins
+```
+
+## Data format
+
+`data/a-hierarchy.xml` is a xml file
+`data/a-synsets.xml` is a xml file
+
+## Usage
+
+The parameters accepted are:
+
+- Language: English (en).
+- Input: Text to analyse.
+
+Example request: 
+```
+http://senpy.cluster.gsi.dit.upm.es/api/?algo=emotion-wnaffect&language=en&input=I%20love%20Madrid
+```
+
+Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section. 
+
+
+The response of this plugin uses [Onyx ontology](https://www.gsi.dit.upm.es/ontologies/onyx/) developed at GSI UPM for semantic web.
+
+This plugin uses WNAffect labels for emotion analysis.
+
+The emotion-wnaffect.senpy file can be copied and modified to use different versions of wnaffect with the same python code.
+
+
+## Known issues
+
+-  This plugin run on **Python2.7** and **Python3.5**
+-  Wnaffect and corpora files are not included in the repository, but can be easily added either to the docker image (using a volume) or in a new docker image. 
+-  You can download Wordnet 1.6 here: <http://wordnetcode.princeton.edu/1.6/wn16.unix.tar.gz> and extract the dict folder. 
+-  The hierarchy and synsets files can be found here: <https://github.com/larsmans/wordnet-domains-sentiwords/tree/master/wn-domains/wn-affect-1.1>
+
+![alt GSI Logo][logoGSI]
+[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
diff --git a/community-plugins/emotion-wnaffect/emotion-wnaffect.py b/community-plugins/emotion-wnaffect/emotion-wnaffect.py
new file mode 100644
index 0000000..2e8840e
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/emotion-wnaffect.py
@@ -0,0 +1,278 @@
+# -*- coding: utf-8 -*-
+from __future__ import division
+import re
+import nltk
+import os
+import string
+import xml.etree.ElementTree as ET
+from nltk.corpus import stopwords
+from nltk.corpus import WordNetCorpusReader
+from nltk.stem import wordnet
+from emotion import Emotion as Emo
+from senpy.plugins import EmotionPlugin, AnalysisPlugin, ShelfMixin
+from senpy.models import Results, EmotionSet, Entry, Emotion
+
+
+class WNAffect(EmotionPlugin, ShelfMixin):
+    '''
+    Emotion classifier using WordNet-Affect to calculate the percentage
+    of each emotion. This plugin classifies among 6 emotions: anger,fear,disgust,joy,sadness
+    or neutral. The only available language is English (en)
+    '''
+    name = 'emotion-wnaffect'
+    author = ["@icorcuera", "@balkian"]
+    version = '0.2'
+    extra_params = {
+      'language': {
+          "@id": 'lang_wnaffect',
+          'description': 'language of the input',
+          'aliases': ['language', 'l'],
+          'required': True,
+          'options': ['en',]
+        }
+    }
+    synsets_path = "a-synsets.xml"
+    hierarchy_path = "a-hierarchy.xml"
+    wn16_path = "wordnet1.6/dict"
+    onyx__usesEmotionModel = "emoml:big6"
+    nltk_resources = ['stopwords', 'averaged_perceptron_tagger', 'wordnet']
+
+    def _load_synsets(self, synsets_path):
+        """Returns a dictionary POS tag -> synset offset -> emotion (str -> int -> str)."""
+        tree = ET.parse(synsets_path)
+        root = tree.getroot()
+        pos_map = {"noun": "NN", "adj": "JJ", "verb": "VB", "adv": "RB"}
+
+        synsets = {}
+        for pos in ["noun", "adj", "verb", "adv"]:
+            tag = pos_map[pos]
+            synsets[tag] = {}
+            for elem in root.findall(
+                    ".//{0}-syn-list//{0}-syn".format(pos, pos)):
+                offset = int(elem.get("id")[2:])
+                if not offset: continue
+                if elem.get("categ"):
+                    synsets[tag][offset] = Emo.emotions[elem.get(
+                        "categ")] if elem.get(
+                            "categ") in Emo.emotions else None
+                elif elem.get("noun-id"):
+                    synsets[tag][offset] = synsets[pos_map["noun"]][int(
+                        elem.get("noun-id")[2:])]
+        return synsets
+
+    def _load_emotions(self, hierarchy_path):
+        """Loads the hierarchy of emotions from the WordNet-Affect xml."""
+
+        tree = ET.parse(hierarchy_path)
+        root = tree.getroot()
+        for elem in root.findall("categ"):
+            name = elem.get("name")
+            if name == "root":
+                Emo.emotions["root"] = Emo("root")
+            else:
+                Emo.emotions[name] = Emo(name, elem.get("isa"))
+
+    def activate(self, *args, **kwargs):
+
+        self._stopwords = stopwords.words('english')
+        self._wnlemma = wordnet.WordNetLemmatizer()
+        self._syntactics = {'N': 'n', 'V': 'v', 'J': 'a', 'S': 's', 'R': 'r'}
+        local_path = os.environ.get("SENPY_DATA")
+        self._categories = {
+            'anger': [
+                'general-dislike',
+            ],
+            'fear': [
+                'negative-fear',
+            ],
+            'disgust': [
+                'shame',
+            ],
+            'joy':
+            ['gratitude', 'affective', 'enthusiasm', 'love', 'joy', 'liking'],
+            'sadness': [
+                'ingrattitude', 'daze', 'humility', 'compassion', 'despair',
+                'anxiety', 'sadness'
+            ]
+        }
+
+        self._wnaffect_mappings = {
+            'anger': 'anger',
+            'fear': 'negative-fear',
+            'disgust': 'disgust',
+            'joy': 'joy',
+            'sadness': 'sadness'
+        }
+
+        self._load_emotions(self.find_file(self.hierarchy_path))
+
+        if 'total_synsets' not in self.sh:
+            total_synsets = self._load_synsets(self.find_file(self.synsets_path))
+            self.sh['total_synsets'] = total_synsets
+
+        self._total_synsets = self.sh['total_synsets']
+
+        self._wn16_path = self.wn16_path
+        self._wn16 = WordNetCorpusReader(self.find_file(self._wn16_path), nltk.data.find(self.find_file(self._wn16_path)))
+
+
+    def deactivate(self, *args, **kwargs):
+        self.save()
+
+    def _my_preprocessor(self, text):
+
+        regHttp = re.compile(
+            '(http://)[a-zA-Z0-9]*.[a-zA-Z0-9/]*(.[a-zA-Z0-9]*)?')
+        regHttps = re.compile(
+            '(https://)[a-zA-Z0-9]*.[a-zA-Z0-9/]*(.[a-zA-Z0-9]*)?')
+        regAt = re.compile('@([a-zA-Z0-9]*[*_/&%#@$]*)*[a-zA-Z0-9]*')
+        text = re.sub(regHttp, '', text)
+        text = re.sub(regAt, '', text)
+        text = re.sub('RT : ', '', text)
+        text = re.sub(regHttps, '', text)
+        text = re.sub('[0-9]', '', text)
+        text = self._delete_punctuation(text)
+        return text
+
+    def _delete_punctuation(self, text):
+
+        exclude = set(string.punctuation)
+        s = ''.join(ch for ch in text if ch not in exclude)
+        return s
+
+    def _extract_ngrams(self, text):
+
+        unigrams_lemmas = []
+        pos_tagged = []
+        unigrams_words = []
+        tokens = text.split()
+        for token in nltk.pos_tag(tokens):
+            unigrams_words.append(token[0])
+            pos_tagged.append(token[1])
+            if token[1][0] in self._syntactics.keys():
+                unigrams_lemmas.append(
+                    self._wnlemma.lemmatize(token[0], self._syntactics[token[1]
+                                                                       [0]]))
+            else:
+                unigrams_lemmas.append(token[0])
+
+        return unigrams_words, unigrams_lemmas, pos_tagged
+
+    def _find_ngrams(self, input_list, n):
+        return zip(*[input_list[i:] for i in range(n)])
+
+    def _clean_pos(self, pos_tagged):
+
+        pos_tags = {
+            'NN': 'NN',
+            'NNP': 'NN',
+            'NNP-LOC': 'NN',
+            'NNS': 'NN',
+            'JJ': 'JJ',
+            'JJR': 'JJ',
+            'JJS': 'JJ',
+            'RB': 'RB',
+            'RBR': 'RB',
+            'RBS': 'RB',
+            'VB': 'VB',
+            'VBD': 'VB',
+            'VGB': 'VB',
+            'VBN': 'VB',
+            'VBP': 'VB',
+            'VBZ': 'VB'
+        }
+
+        for i in range(len(pos_tagged)):
+            if pos_tagged[i] in pos_tags:
+                pos_tagged[i] = pos_tags[pos_tagged[i]]
+        return pos_tagged
+
+    def _extract_features(self, text):
+
+        feature_set = {k: 0 for k in self._categories}
+        ngrams_words, ngrams_lemmas, pos_tagged = self._extract_ngrams(text)
+        matches = 0
+        pos_tagged = self._clean_pos(pos_tagged)
+
+        tag_wn = {
+            'NN': self._wn16.NOUN,
+            'JJ': self._wn16.ADJ,
+            'VB': self._wn16.VERB,
+            'RB': self._wn16.ADV
+        }
+        for i in range(len(pos_tagged)):
+            if pos_tagged[i] in tag_wn:
+                synsets = self._wn16.synsets(ngrams_words[i],
+                                             tag_wn[pos_tagged[i]])
+                if synsets:
+                    offset = synsets[0].offset()
+                    if offset in self._total_synsets[pos_tagged[i]]:
+                        if self._total_synsets[pos_tagged[i]][offset] is None:
+                            continue
+                        else:
+                            emotion = self._total_synsets[pos_tagged[i]][
+                                offset].get_level(5).name
+                            matches += 1
+                            for i in self._categories:
+                                if emotion in self._categories[i]:
+                                    feature_set[i] += 1
+        if matches == 0:
+            matches = 1
+
+        for i in feature_set:
+            feature_set[i] = (feature_set[i] / matches)
+
+        return feature_set
+
+    def analyse_entry(self, entry, activity):
+        params = activity.params
+
+        text_input = entry['nif:isString']
+
+        text = self._my_preprocessor(text_input)
+
+        feature_text = self._extract_features(text)
+
+        emotionSet = EmotionSet(id="Emotions0")
+        emotions = emotionSet.onyx__hasEmotion
+
+        for i in feature_text:
+            emotions.append(
+                Emotion(
+                    onyx__hasEmotionCategory=self._wnaffect_mappings[i],
+                    onyx__hasEmotionIntensity=feature_text[i]))
+
+        entry.emotions = [emotionSet]
+
+        yield entry
+
+
+    def test(self, *args, **kwargs):
+        results = list()
+        params = {'algo': 'emotion-wnaffect', 
+                  'intype': 'direct', 
+                  'expanded-jsonld': 0, 
+                  'informat': 'text', 
+                  'prefix': '', 
+                  'plugin_type': 'analysisPlugin', 
+                  'urischeme': 'RFC5147String', 
+                  'outformat': 'json-ld', 
+                  'i': 'Hello World', 
+                  'input': 'Hello World', 
+                  'conversion': 'full', 
+                  'language': 'en',
+                  'algorithm': 'emotion-wnaffect'}
+        
+        self.activate()
+        texts = {'I hate you': 'anger',
+                 'i am sad': 'sadness',
+                 'i am happy with my marks': 'joy',
+                 'This movie is scary': 'negative-fear'}
+
+        for text in texts:
+            response = next(self.analyse_entry(Entry(nif__isString=text),
+                                               self.activity(params)))
+            expected = texts[text]
+            emotionSet = response.emotions[0]
+            max_emotion = max(emotionSet['onyx:hasEmotion'], key=lambda x: x['onyx:hasEmotionIntensity'])
+            assert max_emotion['onyx:hasEmotionCategory'] == expected
diff --git a/community-plugins/emotion-wnaffect/emotion-wnaffect.senpy b/community-plugins/emotion-wnaffect/emotion-wnaffect.senpy
new file mode 100644
index 0000000..54eea36
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/emotion-wnaffect.senpy
@@ -0,0 +1,6 @@
+---
+module: emotion-wnaffect
+requirements:
+- nltk>=3.0.5
+- lxml>=3.4.2
+async: false
diff --git a/community-plugins/emotion-wnaffect/emotion.py b/community-plugins/emotion-wnaffect/emotion.py
new file mode 100644
index 0000000..d30e35d
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/emotion.py
@@ -0,0 +1,95 @@
+# -*- coding: utf-8 -*-
+"""
+Clement Michard (c) 2015
+"""
+
+class Emotion:
+    """Defines an emotion."""
+    
+    emotions = {} # name to emotion (str -> Emotion)
+    
+    def __init__(self, name, parent_name=None):
+        """Initializes an Emotion object.
+            name -- name of the emotion (str)
+            parent_name -- name of the parent emotion (str)
+        """
+        
+        self.name = name
+        self.parent = None
+        self.level = 0
+        self.children = []
+        
+        if parent_name:
+            self.parent = Emotion.emotions[parent_name] if parent_name else None
+            self.parent.children.append(self)
+            self.level = self.parent.level + 1
+            
+            
+    def get_level(self, level):
+        """Returns the parent of self at the given level.
+            level -- level in the hierarchy (int)        
+        """
+        
+        em = self
+        while em.level > level and em.level >= 0:
+            em = em.parent
+        return em
+    
+    
+    def __str__(self):
+        """Returns the emotion string formatted."""
+        
+        return self.name
+        
+        
+    def nb_children(self):
+        """Returns the number of children of the emotion."""
+        
+        return sum(child.nb_children() for child in self.children) + 1
+        
+        
+    @staticmethod
+    def printTree(emotion=None, indent="", last='updown'):
+        """Prints the hierarchy of emotions.
+            emotion -- root emotion (Emotion)
+        """
+        
+        if not emotion:
+            emotion = Emotion.emotions["root"]
+
+        size_branch = {child: child.nb_children() for child in emotion.children}
+        leaves = sorted(emotion.children, key=lambda emotion: emotion.nb_children())
+        up, down = [], []
+        if leaves:
+            while sum(size_branch[e] for e in down) < sum(size_branch[e] for e in leaves):
+                down.append(leaves.pop())
+            up = leaves
+
+        for leaf in up:     
+            next_last = 'up' if up.index(leaf) is 0 else ''
+            next_indent = '{0}{1}{2}'.format(indent, ' ' if 'up' in last else '│', " " * len(emotion.name))
+            Emotion.printTree(leaf, indent=next_indent, last=next_last)
+        if last == 'up':
+            start_shape = '┌'
+        elif last == 'down':
+            start_shape = '└'
+        elif last == 'updown':
+            start_shape = ' '
+        else:
+            start_shape = '├'
+        if up:
+            end_shape = '┤'
+        elif down:
+            end_shape = '┐'
+        else:
+            end_shape = ''
+        print ('{0}{1}{2}{3}'.format(indent, start_shape, emotion.name, end_shape))
+        for leaf in down:
+            next_last = 'down' if down.index(leaf) is len(down) - 1 else ''
+            next_indent = '{0}{1}{2}'.format(indent, ' ' if 'down' in last else '│', " " * len(emotion.name))
+            Emotion.printTree(leaf, indent=next_indent, last=next_last)
+
+
+
+
+
diff --git a/community-plugins/emotion-wnaffect/wnaffect.py b/community-plugins/emotion-wnaffect/wnaffect.py
new file mode 100644
index 0000000..e6e726c
--- /dev/null
+++ b/community-plugins/emotion-wnaffect/wnaffect.py
@@ -0,0 +1,94 @@
+
+# coding: utf-8
+
+# In[1]:
+
+
+# -*- coding: utf-8 -*-
+"""
+Clement Michard (c) 2015
+"""
+
+import os
+import sys
+import nltk
+from emotion import Emotion
+from nltk.corpus import WordNetCorpusReader
+import xml.etree.ElementTree as ET
+
+class WNAffect:
+    """WordNet-Affect resource."""
+
+    nltk_resources = ['averaged_perceptron_tagger']
+    
+    def __init__(self, wordnet16_dir, wn_domains_dir):
+        """Initializes the WordNet-Affect object."""
+        
+        cwd = os.getcwd()
+        nltk.data.path.append(cwd)
+        wn16_path = "{0}/dict".format(wordnet16_dir)
+        self.wn16 = WordNetCorpusReader(os.path.abspath("{0}/{1}".format(cwd, wn16_path)), nltk.data.find(wn16_path))
+        self.flat_pos = {'NN':'NN', 'NNS':'NN', 'JJ':'JJ', 'JJR':'JJ', 'JJS':'JJ', 'RB':'RB', 'RBR':'RB', 'RBS':'RB', 'VB':'VB', 'VBD':'VB', 'VGB':'VB', 'VBN':'VB', 'VBP':'VB', 'VBZ':'VB'}
+        self.wn_pos = {'NN':self.wn16.NOUN, 'JJ':self.wn16.ADJ, 'VB':self.wn16.VERB, 'RB':self.wn16.ADV}
+        self._load_emotions(wn_domains_dir)
+        self.synsets = self._load_synsets(wn_domains_dir)
+        
+
+
+    def _load_synsets(self, wn_domains_dir):
+        """Returns a dictionary POS tag -> synset offset -> emotion (str -> int -> str)."""
+        
+        tree = ET.parse("{0}/a-synsets.xml".format(wn_domains_dir))
+        root = tree.getroot()
+        pos_map = { "noun": "NN", "adj": "JJ", "verb": "VB", "adv": "RB" }
+    
+        synsets = {}
+        for pos in ["noun", "adj", "verb", "adv"]:
+            tag = pos_map[pos]
+            synsets[tag] = {}
+            for elem in root.findall(".//{0}-syn-list//{0}-syn".format(pos, pos)):
+                offset = int(elem.get("id")[2:])                
+                if not offset: continue
+                if elem.get("categ"):
+                    synsets[tag][offset] = Emotion.emotions[elem.get("categ")] if elem.get("categ") in Emotion.emotions else None
+                elif elem.get("noun-id"):
+                    synsets[tag][offset] = synsets[pos_map["noun"]][int(elem.get("noun-id")[2:])]
+    
+        return synsets
+        
+    def _load_emotions(self, wn_domains_dir):
+        """Loads the hierarchy of emotions from the WordNet-Affect xml."""
+        
+        tree = ET.parse("{0}/a-hierarchy.xml".format(wn_domains_dir))
+        root = tree.getroot()
+        for elem in root.findall("categ"):
+            name = elem.get("name")
+            if name == "root":
+                Emotion.emotions["root"] = Emotion("root")
+            else:
+                Emotion.emotions[name] = Emotion(name, elem.get("isa"))
+    
+    def get_emotion(self, word, pos):
+        """Returns the emotion of the word.
+            word -- the word (str)
+            pos -- part-of-speech (str)
+        """
+        
+        if pos in self.flat_pos:
+            pos = self.flat_pos[pos]
+            synsets = self.wn16.synsets(word, self.wn_pos[pos])         
+            if synsets:
+                offset = synsets[0].offset()
+                if offset in self.synsets[pos]:
+                    return self.synsets[pos][offset]
+        return None
+
+            
+
+            
+if __name__ == "__main__":
+    wordnet16, wndomains32, word, pos = sys.argv[1:5]
+    wna = WNAffect(wordnet16, wndomains32)
+    print wna.get_emotion(word, pos)
+
+
diff --git a/community-plugins/example-plugin/example_plugin.py b/community-plugins/example-plugin/example_plugin.py
new file mode 100644
index 0000000..635ea94
--- /dev/null
+++ b/community-plugins/example-plugin/example_plugin.py
@@ -0,0 +1,36 @@
+from senpy.plugins import AnalysisPlugin
+from senpy.models import Response, Entry
+
+
+class ExamplePlugin(AnalysisPlugin):
+    '''A *VERY* simple plugin that exemplifies the development of Senpy Plugins'''
+    name = "example-plugin"
+    author = "@balkian"
+    version = "0.1"
+    extra_params = {
+        "parameter": {
+            "@id": "parameter",
+            "description": "this parameter does nothing, it is only an example",
+            "aliases": ["parameter", "param"],
+            "required": True,
+            "default": 42
+        }
+      }
+    custom_attribute = "42"
+
+    def analyse_entry(self, entry, activity):
+        params = activity.params
+        self.log.debug('Analysing with the example.')
+        self.log.debug('The answer to this response is: %s.' % params['parameter'])
+        resp = Response()
+        entry['example:reversed'] = entry.text[::-1]
+        entry['example:the_answer'] = params['parameter']
+
+        yield entry
+
+    test_cases = [{
+        'input': 'hello',
+        'expected': {
+            'example:reversed': 'olleh'
+        }
+    }]
diff --git a/community-plugins/k8s/README.md b/community-plugins/k8s/README.md
new file mode 100644
index 0000000..175beec
--- /dev/null
+++ b/community-plugins/k8s/README.md
@@ -0,0 +1,8 @@
+Deploy senpy to a kubernetes cluster.
+The files are templates, which need to be expanded with something like envsubst.
+
+Example usage:
+
+```
+cat k8s/*.ya*ml | envsubst | kubectl apply -n senpy -f -
+```
diff --git a/community-plugins/k8s/senpy-deployment.yaml b/community-plugins/k8s/senpy-deployment.yaml
new file mode 100644
index 0000000..672e43e
--- /dev/null
+++ b/community-plugins/k8s/senpy-deployment.yaml
@@ -0,0 +1,36 @@
+---
+apiVersion: extensions/v1beta1
+kind: Deployment
+metadata:
+  name: senpy-$NAME-latest
+spec:
+  replicas: 1
+  template:
+    metadata:
+      labels:
+        role: $NAME-latest
+        app: test
+    spec:
+      containers:
+      - name: senpy-latest
+        image: $IMAGEWTAG
+        imagePullPolicy: Always
+        resources:
+          limits:
+            memory: "2048Mi"
+            cpu: "1000m"
+        ports:
+          - name: web
+            containerPort: 5000
+        volumeMounts:
+          # name must match the volume name below
+          - name: senpy-data
+            mountPath: "/data"
+            subPath: data
+        env:
+          - name: SENPY_DATA
+            value: '/data'
+      volumes:
+      - name: senpy-data
+        persistentVolumeClaim:
+          claimName: senpy-pvc
diff --git a/community-plugins/k8s/senpy-ingress.yaml b/community-plugins/k8s/senpy-ingress.yaml
new file mode 100644
index 0000000..a12d059
--- /dev/null
+++ b/community-plugins/k8s/senpy-ingress.yaml
@@ -0,0 +1,24 @@
+---
+apiVersion: extensions/v1beta1
+kind: Ingress
+metadata:
+  name: senpy-$NAME-ingress
+  annotations:
+    ingress.kubernetes.io/proxy-body-size: 0m
+    ingress.kubernetes.io/proxy-buffer-size: "256k"
+spec:
+  rules:
+  - host: senpy.cluster.gsi.dit.upm.es
+    http:
+      paths:
+      - path: /
+        backend:
+          serviceName: senpy-$NAME-latest
+          servicePort: 5000
+  - host: senpy.gsi.upm.es
+    http:
+      paths:
+      - path: /
+        backend:
+          serviceName: senpy-$NAME-latest
+          servicePort: 5000
diff --git a/community-plugins/k8s/senpy-svc.yaml b/community-plugins/k8s/senpy-svc.yaml
new file mode 100644
index 0000000..4dac88f
--- /dev/null
+++ b/community-plugins/k8s/senpy-svc.yaml
@@ -0,0 +1,12 @@
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: senpy-$NAME-latest
+spec:
+  type: ClusterIP
+  ports:
+    - port: 5000
+      protocol: TCP
+  selector:
+    role: $NAME-latest
diff --git a/community-plugins/sentiment-basic/README.md b/community-plugins/sentiment-basic/README.md
new file mode 100755
index 0000000..701af8d
--- /dev/null
+++ b/community-plugins/sentiment-basic/README.md
@@ -0,0 +1,28 @@
+# Sentiment basic plugin
+
+This plugin is based on the classifier developed for the TASS 2015 competition. It has been developed for Spanish and English. This is a demo plugin that uses only some features from the TASS 2015 classifier. To use the entirely functional classifier you can use the service in: http://senpy.cluster.gsi.dit.upm.es
+
+There is more information avaliable in:
+	
+	- Aspect based Sentiment Analysis of Spanish Tweets, Oscar Araque and Ignacio Corcuera-Platas and Constantino Román-Gómez and Carlos A. Iglesias and J. Fernando Sánchez-Rada. http://gsi.dit.upm.es/es/investigacion/publicaciones?view=publication&task=show&id=376
+
+## Usage
+Params accepted:
+
+- Language: Spanish (es).
+- Input: text to analyse.
+
+
+Example request: 
+```
+http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-basic&language=es&input=I%20love%20Madrid
+```
+
+Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section. 
+
+This plugin only supports **python2**
+
+
+![alt GSI Logo][logoGSI]
+
+[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
diff --git a/community-plugins/sentiment-basic/sentiment-basic.py b/community-plugins/sentiment-basic/sentiment-basic.py
new file mode 100644
index 0000000..60e2af2
--- /dev/null
+++ b/community-plugins/sentiment-basic/sentiment-basic.py
@@ -0,0 +1,177 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+import os
+import sys
+import string
+import nltk
+import pickle
+
+from sentiwn import SentiWordNet
+from nltk.corpus import wordnet as wn
+from textblob import TextBlob
+from scipy.interpolate import interp1d
+from os import path
+
+from senpy.plugins import SentimentBox, SenpyPlugin
+from senpy.models import Results, Entry, Sentiment, Error
+
+if sys.version_info[0] >= 3:
+    unicode = str
+
+
+class SentimentBasic(SentimentBox):
+    '''
+    Sentiment classifier using rule-based classification for Spanish. Based on english to spanish translation and SentiWordNet sentiment knowledge. This is a demo plugin that uses only some features from the TASS 2015 classifier. To use the entirely functional classifier you can use the service in: http://senpy.cluster.gsi.dit.upm.es.
+    '''
+    name = "sentiment-basic"
+    author = "github.com/nachtkatze"
+    version = "0.1.1"
+    extra_params = {
+        "language": {
+            "description": "language of the text",
+            "aliases": ["language", "l"],
+            "required": True,
+            "options": ["en","es", "it", "fr"],
+            "default": "en"
+        }
+    }
+    sentiword_path = "SentiWordNet_3.0.txt"
+    pos_path = "unigram_spanish.pickle"
+    maxPolarityValue = 1
+    minPolarityValue = -1
+    nltk_resources = ['punkt','wordnet', 'omw']
+
+    with_polarity = False
+
+    def _load_swn(self):
+        self.swn_path = self.find_file(self.sentiword_path)
+        swn = SentiWordNet(self.swn_path)
+        return swn
+
+    def _load_pos_tagger(self):
+        self.pos_path = self.find_file(self.pos_path)
+        with open(self.pos_path, 'rb') as f:
+            tagger = pickle.load(f)
+        return tagger
+
+    def activate(self, *args, **kwargs):
+        self._swn = self._load_swn()
+        self._pos_tagger = self._load_pos_tagger()
+
+    def _remove_punctuation(self, tokens):
+        return [t for t in tokens if t not in string.punctuation]
+
+    def _tokenize(self, text):
+        sentence_ = {}
+        words = nltk.word_tokenize(text)
+        sentence_['sentence'] = text
+        tokens_ = [w.lower() for w in words]
+        sentence_['tokens'] = self._remove_punctuation(tokens_)
+        return sentence_
+
+    def _pos(self, tokens):
+        tokens['tokens'] = self._pos_tagger.tag(tokens['tokens'])
+        return tokens
+
+    def _compare_synsets(self, synsets, tokens):
+        for synset in synsets:
+            for word, lemmas in tokens['lemmas'].items():
+                for lemma in lemmas:
+                    synset_ = lemma.synset() 
+                    if synset == synset_:
+                        return synset
+        return None
+
+    def predict_one(self, features, activity):
+        language = activity.param("language")
+        text = features[0]
+        tokens = self._tokenize(text)
+        tokens = self._pos(tokens)
+        sufixes = {'es':'spa','en':'eng','it':'ita','fr':'fra'}
+        tokens['lemmas'] = {}
+        for w in tokens['tokens']:
+            lemmas = wn.lemmas(w[0], lang=sufixes[language])
+            if len(lemmas) == 0:
+                continue
+            tokens['lemmas'][w[0]] = lemmas
+        if language == "en":
+            trans = TextBlob(unicode(text))
+        else:
+            try:
+                trans = TextBlob(unicode(text)).translate(from_lang=language,to='en')
+            except Exception as ex:
+                raise Error('Could not translate the text from "{}" to "{}": {}'.format(language,
+                                                                                    'en',
+                                                                                    str(ex)))
+        useful_synsets = {}
+        for w_i, t_w in enumerate(trans.sentences[0].words):
+            synsets = wn.synsets(trans.sentences[0].words[w_i])
+            if len(synsets) == 0:
+                continue
+            eq_synset = self._compare_synsets(synsets, tokens)
+            useful_synsets[t_w] = eq_synset
+        scores = {}
+        scores = {}
+        if useful_synsets != None:
+            for word in useful_synsets:
+                if useful_synsets[word] is None:
+                    continue
+                temp_scores = self._swn.get_score(useful_synsets[word].name().split('.')[0].replace(' ',' '))
+                for score in temp_scores:
+                    if score['synset'] == useful_synsets[word]:
+                        t_score = score['pos'] - score['neg']
+                        f_score = 'neu'
+                        if t_score > 0:
+                            f_score = 'pos'
+                        elif t_score < 0:
+                            f_score = 'neg'
+                        score['score'] = f_score
+                        scores[word] = score
+                        break
+        g_score = 0.5
+
+        for i in scores:
+            n_pos = 0.0
+            n_neg = 0.0
+            for w in scores:
+                if scores[w]['score'] == 'pos':
+                    n_pos += 1.0
+                elif scores[w]['score'] == 'neg':
+                    n_neg += 1.0
+            inter = interp1d([-1.0, 1.0], [0.0, 1.0])
+
+            try:
+                g_score = (n_pos - n_neg) / (n_pos + n_neg)
+                g_score = float(inter(g_score))
+            except:
+                if n_pos == 0 and n_neg == 0:
+                    g_score = 0.5
+
+        if g_score > 0.5:  # Positive
+            return [1, 0, 0]
+        elif g_score < 0.5:  # Negative
+            return [0, 0, 1]
+        else:
+            return [0, 1, 0]
+
+
+    test_cases = [
+        {
+            'input': 'Odio ir al cine',
+            'params': {'language': 'es'},
+            'polarity': 'marl:Negative'
+
+        },
+        {
+            'input': 'El cielo está nublado',
+            'params': {'language': 'es'},
+            'polarity': 'marl:Neutral'
+
+        },
+        {
+            'input': 'Esta tarta está muy buena',
+            'params': {'language': 'es'},
+            'polarity': 'marl:Negative' # SURPRISINGLY!
+
+        }
+    ]
diff --git a/community-plugins/sentiment-basic/sentiment-basic.senpy b/community-plugins/sentiment-basic/sentiment-basic.senpy
new file mode 100644
index 0000000..fee2f7c
--- /dev/null
+++ b/community-plugins/sentiment-basic/sentiment-basic.senpy
@@ -0,0 +1,7 @@
+---
+module: sentiment-basic
+requirements:
+- nltk>=3.0.5
+- scipy>=0.14.0
+- textblob
+
diff --git a/community-plugins/sentiment-basic/sentiwn.py b/community-plugins/sentiment-basic/sentiwn.py
new file mode 100644
index 0000000..6f192b5
--- /dev/null
+++ b/community-plugins/sentiment-basic/sentiwn.py
@@ -0,0 +1,70 @@
+#!/usr/bin/env python
+"""
+Author : Jaganadh Gopinadhan <jaganadhg@gmail.com>
+Copywright (C) : Jaganadh Gopinadhan
+
+ Apache License, Version 2.0
+  (the "License"); you may not use this file except in compliance with
+  the License.  You may obtain a copy of the License at
+ 
+      http://www.apache.org/licenses/LICENSE-2.0
+ 
+  Unless required by applicable law or agreed to in writing, software
+  distributed under the License is distributed on an "AS IS" BASIS,
+  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+  See the License for the specific language governing permissions and
+  limitations under the License.
+"""
+
+import sys,os
+import re
+
+from nltk.corpus import wordnet
+
+class SentiWordNet(object):
+    """
+    Interface to SentiWordNet
+    """
+    def __init__(self,swn_file):
+        """
+        """
+        self.swn_file = swn_file
+        self.pos_synset = self.__parse_swn_file()
+
+    def __parse_swn_file(self):
+        """
+        Parse the SentiWordNet file and populate the POS and SynsetID hash
+        """
+        pos_synset_hash = {}
+        swn_data = open(self.swn_file,'r').readlines()
+        head_less_swn_data = filter((lambda line: not re.search(r"^\s*#",\
+        line)), swn_data)
+
+        for data in head_less_swn_data:
+            fields = data.strip().split("\t")
+            try:
+                pos,syn_set_id,pos_score,neg_score,syn_set_score,\
+                gloss = fields
+            except:
+                print("Found data without all details")
+                pass
+
+            if pos and syn_set_score:
+                pos_synset_hash[(pos,int(syn_set_id))] = (float(pos_score),\
+                float(neg_score))
+
+        return pos_synset_hash
+
+    def get_score(self,word,pos=None):
+        """
+        Get score for a given word/word pos combination
+        """
+        senti_scores = []
+        synsets = wordnet.synsets(word,pos)
+        for synset in synsets:
+            if (synset.pos(), synset.offset()) in self.pos_synset:
+                pos_val, neg_val = self.pos_synset[(synset.pos(), synset.offset())]
+                senti_scores.append({"pos":pos_val,"neg":neg_val,\
+                "obj": 1.0 - (pos_val - neg_val),'synset':synset})
+
+        return senti_scores
diff --git a/community-plugins/sentiment-meaningCloud/.gitignore b/community-plugins/sentiment-meaningCloud/.gitignore
new file mode 100644
index 0000000..b3992d9
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.gitignore
@@ -0,0 +1,5 @@
+.*
+.env
+__pycache__
+.pyc
+VERSION
diff --git a/community-plugins/sentiment-meaningCloud/.gitlab-ci.yml b/community-plugins/sentiment-meaningCloud/.gitlab-ci.yml
new file mode 100644
index 0000000..4806968
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.gitlab-ci.yml
@@ -0,0 +1,67 @@
+# Uncomment if you want to use docker-in-docker
+# image: gsiupm/dockermake:latest
+# services:
+# - docker:dind
+# When using dind, it's wise to use the overlayfs driver for
+# improved performance.
+
+stages:
+  - test
+  - push
+  - deploy
+  - clean
+
+before_script:
+  - make -e login
+
+.test: &test_definition
+  stage: test
+  script:
+    - make -e test-$PYTHON_VERSION
+
+test-3.5:
+  <<: *test_definition
+  variables:
+    PYTHON_VERSION: "3.5"
+
+.image: &image_definition
+  stage: push
+  script:
+    - make -e push-$PYTHON_VERSION
+  only:
+    - tags
+    - triggers
+
+push-3.5:
+  <<: *image_definition
+  variables:
+    PYTHON_VERSION: "3.5"
+
+push-latest:
+  <<: *image_definition
+  variables:
+    PYTHON_VERSION: latest
+  only:
+    - tags
+    - triggers
+
+deploy:
+  stage: deploy
+  environment: production
+  script:
+    - make -e deploy
+  only:
+    - tags
+    - triggers
+
+clean :
+  stage: clean
+  script:
+    - make -e clean
+  when: manual
+
+cleanup_py:
+   stage: clean
+   when: always   # this is important; run even if preceding stages failed.
+   script:
+    - docker logout
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/README.md b/community-plugins/sentiment-meaningCloud/.makefiles/README.md
new file mode 100644
index 0000000..2ab487e
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/README.md
@@ -0,0 +1,27 @@
+These makefiles are recipes for several common tasks in different types of projects.
+To add them to your project, simply do:
+
+```
+git remote add makefiles ssh://git@lab.cluster.gsi.dit.upm.es:2200/docs/templates/makefiles.git
+git subtree add --prefix=.makefiles/ makefiles master
+touch Makefile
+echo "include .makefiles/base.mk" >> Makefile
+```
+
+Now you can take advantage of the recipes.
+For instance, to add useful targets for a python project, just add this to your Makefile:
+
+```
+include .makefiles/python.mk
+```
+
+You may need to set special variables like the name of your project or the python versions you're targetting.
+Take a look at each specific `.mk` file for more information, and the `Makefile` in the [senpy](https://lab.cluster.gsi.dit.upm.es/senpy/senpy) project for a real use case.
+
+If you update the makefiles from your repository, make sure to push the changes for review in upstream (this repository):
+
+```
+make makefiles-push
+```
+
+It will automatically commit all unstaged changes in the .makefiles folder.
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/base.mk b/community-plugins/sentiment-meaningCloud/.makefiles/base.mk
new file mode 100644
index 0000000..a4d94d7
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/base.mk
@@ -0,0 +1,36 @@
+export
+NAME ?= $(shell basename $(CURDIR))
+VERSION ?= $(shell git describe --tags --dirty 2>/dev/null)
+
+ifeq ($(VERSION),)
+	VERSION:="unknown"
+endif
+
+# Get the location of this makefile.
+MK_DIR := $(dir $(abspath $(lastword $(MAKEFILE_LIST))))
+
+-include .env
+-include ../.env
+
+help:           ## Show this help.
+	@fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/\(.*:\)[^#]*##\s*\(.*\)/\1\t\2/' | column -t -s "	"
+
+config:  ## Load config from the environment. You should run it once in every session before other tasks. Run: eval $(make config)
+	@awk '{ print "export " $$0}' ../.env
+	@awk '{ print "export " $$0}' .env
+	@echo "# Please, run: "
+	@echo "# eval \$$(make config)"
+# If you need to run a command on the key/value pairs, use this:
+# @awk '{ split($$0, a, "="); "echo " a[2] " | base64 -w 0" |& getline b64; print "export " a[1] "=" a[2]; print "export " a[1] "_BASE64=" b64}' .env
+
+ci:  ## Run a task using gitlab-runner. Only use to debug problems in the CI pipeline
+	gitlab-runner exec shell --builds-dir '.builds' --env CI_PROJECT_NAME=$(NAME) ${action}
+
+include $(MK_DIR)/makefiles.mk
+include $(MK_DIR)/docker.mk
+include $(MK_DIR)/git.mk
+
+info:: ## List all variables
+	env
+
+.PHONY:: config help ci
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/docker.mk b/community-plugins/sentiment-meaningCloud/.makefiles/docker.mk
new file mode 100644
index 0000000..f74d93f
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/docker.mk
@@ -0,0 +1,29 @@
+IMAGENAME?=$(NAME)
+IMAGEWTAG?=$(IMAGENAME):$(VERSION)
+
+docker-login: ## Log in to the registry. It will only be used in the server, or when running a CI task locally (if CI_BUILD_TOKEN is set).
+ifeq ($(CI_BUILD_TOKEN),)
+	@echo "Not logging in to the docker registry" "$(CI_REGISTRY)"
+else
+	@docker login -u gitlab-ci-token -p $(CI_BUILD_TOKEN) $(CI_REGISTRY)
+endif
+ifeq ($(HUB_USER),)
+	@echo "Not logging in to global the docker registry"
+else
+	@docker login -u $(HUB_USER) -p $(HUB_PASSWORD)
+endif
+
+docker-clean: ## Remove docker credentials
+ifeq ($(HUB_USER),)
+else
+	@docker logout
+endif
+
+login:: docker-login
+
+clean:: docker-clean
+
+docker-info:
+	@echo IMAGEWTAG=${IMAGEWTAG}
+
+.PHONY:: docker-login docker-clean login clean
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/git.mk b/community-plugins/sentiment-meaningCloud/.makefiles/git.mk
new file mode 100644
index 0000000..836eb14
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/git.mk
@@ -0,0 +1,28 @@
+commit:
+	git commit -a
+
+tag:
+	git tag ${VERSION}
+
+git-push::
+	git push --tags -u origin HEAD
+
+git-pull:
+	git pull --all
+
+push-github: ## Push the code to github. You need to set up GITHUB_DEPLOY_KEY
+ifeq ($(GITHUB_DEPLOY_KEY),)
+else
+	$(eval KEY_FILE := "$(shell mktemp)")
+	@echo "$(GITHUB_DEPLOY_KEY)" > $(KEY_FILE)
+	@git remote rm github-deploy || true
+	git remote add github-deploy $(GITHUB_REPO)
+	-@GIT_SSH_COMMAND="ssh -i $(KEY_FILE)" git fetch github-deploy $(CI_COMMIT_REF_NAME)
+	@GIT_SSH_COMMAND="ssh -i $(KEY_FILE)" git push github-deploy HEAD:$(CI_COMMIT_REF_NAME)
+	rm $(KEY_FILE)
+endif
+
+push:: git-push
+pull:: git-pull
+
+.PHONY:: commit tag push git-push git-pull push-github 
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/k8s.mk b/community-plugins/sentiment-meaningCloud/.makefiles/k8s.mk
new file mode 100644
index 0000000..a493b4a
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/k8s.mk
@@ -0,0 +1,51 @@
+# Deployment with Kubernetes
+
+# KUBE_CA_PEM_FILE is the path of a certificate file. It automatically set by GitLab
+# if you enable Kubernetes integration in a project.
+#
+# As of this writing, Kubernetes integration can not be set on a group level, so it has to
+# be manually set in every project.
+# Alternatively, we use a custom KUBE_CA_BUNDLE environment variable, which can be set at
+# the group level. In this case, the variable contains the whole content of the certificate,
+# which we dump to a temporary file
+#
+# Check if the KUBE_CA_PEM_FILE exists. Otherwise, create it from KUBE_CA_BUNDLE
+KUBE_CA_TEMP=false
+ifndef KUBE_CA_PEM_FILE
+KUBE_CA_PEM_FILE:=$$PWD/.ca.crt
+CREATED:=$(shell echo -e "$(KUBE_CA_BUNDLE)" > $(KUBE_CA_PEM_FILE))
+endif 
+KUBE_TOKEN?=""
+KUBE_NAMESPACE?=$(NAME)
+KUBECTL=docker run --rm -v $(KUBE_CA_PEM_FILE):/tmp/ca.pem -i lachlanevenson/k8s-kubectl --server="$(KUBE_URL)" --token="$(KUBE_TOKEN)" --certificate-authority="/tmp/ca.pem" -n $(KUBE_NAMESPACE)
+CI_COMMIT_REF_NAME?=master
+
+info:: ## Print variables. Useful for debugging.
+	@echo "#KUBERNETES"
+	@echo KUBE_URL=$(KUBE_URL)
+	@echo KUBE_CA_PEM_FILE=$(KUBE_CA_PEM_FILE)
+	@echo KUBE_CA_BUNDLE=$$KUBE_CA_BUNDLE
+	@echo KUBE_TOKEN=$(KUBE_TOKEN)
+	@echo KUBE_NAMESPACE=$(KUBE_NAMESPACE)
+	@echo KUBECTL=$(KUBECTL)
+
+	@echo "#CI"
+	@echo CI_PROJECT_NAME=$(CI_PROJECT_NAME)
+	@echo CI_REGISTRY=$(CI_REGISTRY)
+	@echo CI_REGISTRY_USER=$(CI_REGISTRY_USER)
+	@echo CI_COMMIT_REF_NAME=$(CI_COMMIT_REF_NAME)
+	@echo "CREATED=$(CREATED)"
+
+#
+# Deployment and advanced features
+# 
+
+
+deploy: ## Deploy to kubernetes using the credentials in KUBE_CA_PEM_FILE (or KUBE_CA_BUNDLE ) and TOKEN
+	@ls k8s/*.yaml k8s/*.yml k8s/*.tmpl 2>/dev/null || true
+	@cat k8s/*.yaml k8s/*.yml k8s/*.tmpl 2>/dev/null | envsubst | $(KUBECTL) apply -f -
+
+deploy-check: ## Get the deployed configuration.
+	@$(KUBECTL) get deploy,pods,svc,ingress
+
+.PHONY:: info deploy deploy-check
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/makefiles.mk b/community-plugins/sentiment-meaningCloud/.makefiles/makefiles.mk
new file mode 100644
index 0000000..03dcc17
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/makefiles.mk
@@ -0,0 +1,17 @@
+makefiles-remote:
+	@git remote add makefiles ssh://git@lab.cluster.gsi.dit.upm.es:2200/docs/templates/makefiles.git 2>/dev/null || true
+
+makefiles-commit: makefiles-remote
+	git add -f .makefiles
+	git commit -em "Updated makefiles from ${NAME}"
+
+makefiles-push:
+	git subtree push --prefix=.makefiles/ makefiles $(NAME)
+
+makefiles-pull: makefiles-remote
+	git subtree pull --prefix=.makefiles/ makefiles master --squash
+
+pull:: makefiles-pull
+push:: makefiles-push
+
+.PHONY:: makefiles-remote makefiles-commit makefiles-push makefiles-pull pull push
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/precommit.mk b/community-plugins/sentiment-meaningCloud/.makefiles/precommit.mk
new file mode 100644
index 0000000..82fe75f
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/precommit.mk
@@ -0,0 +1,5 @@
+init: ## Init pre-commit hooks (i.e. enforcing format checking before allowing a commit)
+	pip install --user pre-commit
+	pre-commit install
+
+.PHONY:: init
diff --git a/community-plugins/sentiment-meaningCloud/.makefiles/python.mk b/community-plugins/sentiment-meaningCloud/.makefiles/python.mk
new file mode 100644
index 0000000..2ad9559
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/.makefiles/python.mk
@@ -0,0 +1,100 @@
+PYVERSIONS ?= 3.5
+PYMAIN ?= $(firstword $(PYVERSIONS))
+TARNAME ?= $(NAME)-$(VERSION).tar.gz 
+VERSIONFILE ?= $(NAME)/VERSION
+
+DEVPORT ?= 6000
+
+
+.FORCE:
+
+version: .FORCE
+	@echo $(VERSION) > $(VERSIONFILE)
+	@echo $(VERSION)
+
+yapf: ## Format python code
+	yapf -i -r $(NAME)
+	yapf -i -r tests
+
+dockerfiles: $(addprefix Dockerfile-,$(PYVERSIONS)) ## Generate dockerfiles for each python version
+	@unlink Dockerfile >/dev/null
+	ln -s Dockerfile-$(PYMAIN) Dockerfile
+
+Dockerfile-%: Dockerfile.template  ## Generate a specific dockerfile (e.g. Dockerfile-2.7)
+	sed "s/{{PYVERSION}}/$*/" Dockerfile.template > Dockerfile-$*
+
+quick_build: $(addprefix build-, $(PYMAIN))
+
+build: $(addprefix build-, $(PYVERSIONS)) ## Build all images / python versions
+
+build-%: version Dockerfile-%  ## Build a specific version (e.g. build-2.7)
+	docker build -t '$(IMAGEWTAG)-python$*' --cache-from $(IMAGENAME):python$* -f Dockerfile-$* .;
+
+dev-%: ## Launch a specific development environment using docker (e.g. dev-2.7)
+	@docker start $(NAME)-dev$* || (\
+		$(MAKE) build-$*; \
+		docker run -d -w /usr/src/app/ -p $(DEVPORT):5000 -v $$PWD:/usr/src/app --entrypoint=/bin/bash -ti --name $(NAME)-dev$* '$(IMAGEWTAG)-python$*'; \
+	)\
+
+	docker exec -ti $(NAME)-dev$* bash
+
+dev: dev-$(PYMAIN) ## Launch a development environment using docker, using the default python version
+
+quick_test: test-$(PYMAIN)
+
+test-%: ## Run setup.py from in an isolated container, built from the base image. (e.g. test-2.7)
+# This speeds tests up because the image has most (if not all) of the dependencies already.
+	docker rm $(NAME)-test-$* || true
+	docker create -ti --name $(NAME)-test-$* --entrypoint="" -w /usr/src/app/ $(IMAGENAME):python$* python setup.py test
+	docker cp . $(NAME)-test-$*:/usr/src/app
+	docker start -a $(NAME)-test-$*
+
+test: $(addprefix test-,$(PYVERSIONS)) ## Run the tests with the main python version
+
+run-%: build-%
+	docker run --rm -p $(DEVPORT):5000 -ti '$(IMAGEWTAG)-python$(PYMAIN)' --default-plugins
+
+run: run-$(PYMAIN)
+
+# Pypy - Upload a package
+
+dist/$(TARNAME): version
+	python setup.py sdist;
+
+sdist: dist/$(TARNAME) ## Generate the distribution file (wheel)
+
+pip_test-%: sdist ## Test the distribution file using pip install and a specific python version (e.g. pip_test-2.7)
+	docker run --rm -v $$PWD/dist:/dist/ python:$* pip install /dist/$(TARNAME);
+
+pip_test: $(addprefix pip_test-,$(PYVERSIONS)) ## Test pip installation with the main python version
+
+pip_upload: pip_test  ## Upload package to pip
+	python setup.py sdist upload ;
+
+# Pushing to docker
+
+push-latest: $(addprefix push-latest-,$(PYVERSIONS)) ## Push the "latest" tag to dockerhub
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGEWTAG)'
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGENAME)'
+	docker push '$(IMAGENAME):latest'
+	docker push '$(IMAGEWTAG)'
+
+push-latest-%: build-%  ## Push the latest image for a specific python version
+	docker tag $(IMAGENAME):$(VERSION)-python$* $(IMAGENAME):python$*
+	docker push $(IMAGENAME):$(VERSION)-python$*
+	docker push $(IMAGENAME):python$*
+
+push-%: build-%  ## Push the image of the current version (tagged). e.g. push-2.7
+	docker push $(IMAGENAME):$(VERSION)-python$*
+
+push:: $(addprefix push-,$(PYVERSIONS)) ## Push an image with the current version for every python version
+	docker tag '$(IMAGEWTAG)-python$(PYMAIN)' '$(IMAGEWTAG)'
+	docker push  $(IMAGENAME):$(VERSION)
+
+clean:: ## Clean older docker images and containers related to this project and dev environments
+	@docker stop $(addprefix $(NAME)-dev,$(PYVERSIONS)) 2>/dev/null || true
+	@docker rm $(addprefix $(NAME)-dev,$(PYVERSIONS)) 2>/dev/null || true
+	@docker ps -a | grep $(IMAGENAME) | awk '{ split($$2, vers, "-"); if(vers[0] != "${VERSION}"){ print $$1;}}' | xargs docker rm -v 2>/dev/null|| true
+	@docker images | grep $(IMAGENAME) | awk '{ split($$2, vers, "-"); if(vers[0] != "${VERSION}"){ print $$1":"$$2;}}' | xargs docker rmi 2>/dev/null|| true
+
+.PHONY:: yapf dockerfiles Dockerfile-% quick_build build build-% dev-% quick-dev test quick_test push-latest push-latest-% push-% push version .FORCE
diff --git a/community-plugins/sentiment-meaningCloud/Dockerfile b/community-plugins/sentiment-meaningCloud/Dockerfile
new file mode 120000
index 0000000..89e531a
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/Dockerfile
@@ -0,0 +1 @@
+Dockerfile-3.5
\ No newline at end of file
diff --git a/community-plugins/sentiment-meaningCloud/Dockerfile-3.5 b/community-plugins/sentiment-meaningCloud/Dockerfile-3.5
new file mode 100644
index 0000000..100885d
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/Dockerfile-3.5
@@ -0,0 +1,4 @@
+FROM gsiupm/senpy:0.10.4-python3.5
+
+
+MAINTAINER manuel.garcia-amado.sancho@alumnos.upm.es
diff --git a/community-plugins/sentiment-meaningCloud/Dockerfile.template b/community-plugins/sentiment-meaningCloud/Dockerfile.template
new file mode 100644
index 0000000..453ae95
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/Dockerfile.template
@@ -0,0 +1,4 @@
+FROM gsiupm/senpy:0.10.4-python{{PYVERSION}}
+
+
+MAINTAINER manuel.garcia-amado.sancho@alumnos.upm.es
diff --git a/community-plugins/sentiment-meaningCloud/Makefile b/community-plugins/sentiment-meaningCloud/Makefile
new file mode 100644
index 0000000..444c94b
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/Makefile
@@ -0,0 +1,9 @@
+NAME:=meaningcloud
+VERSIONFILE:=VERSION
+IMAGENAME:=registry.cluster.gsi.dit.upm.es/senpy/sentiment-meaningcloud
+PYVERSIONS:= 3.5
+DEVPORT:=5000
+
+include .makefiles/base.mk
+include .makefiles/k8s.mk
+include .makefiles/python.mk
diff --git a/community-plugins/sentiment-meaningCloud/README.md b/community-plugins/sentiment-meaningCloud/README.md
new file mode 100644
index 0000000..5bbb7a0
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/README.md
@@ -0,0 +1,34 @@
+# Senpy Plugin MeaningCloud
+
+MeaningCloud plugin uses API from Meaning Cloud to perform sentiment analysis. 
+
+For more information about Meaning Cloud and its services, please visit: https://www.meaningcloud.com/developer/apis
+
+## Usage
+
+To use this plugin, you need to obtain an API key from meaningCloud signing up here: https://www.meaningcloud.com/developer/login
+
+When you had obtained the meaningCloud API Key, you have to provide it to the plugin, using the param **apiKey**.
+
+To use this plugin, you should use a GET Requests with the following possible params:
+Params:	
+- Language: English (en) and Spanish (es). (default: en)
+- API Key: the API key from Meaning Cloud. Aliases: ["apiKey","meaningCloud-key"]. (required)
+- Input: text to analyse.(required)
+- Model: model provided to Meaning Cloud API (for general domain). (default: general)
+
+## Example of Usage
+
+Example request: 
+```
+http://senpy.cluster.gsi.dit.upm.es/api/?algo=meaningCloud&language=en&apiKey=<put here your API key>&input=I%20love%20Madrid
+```
+
+
+Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section. 
+
+This plugin supports **python2.7** and **python3**.
+
+![alt GSI Logo][logoGSI]
+
+[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
diff --git a/community-plugins/sentiment-meaningCloud/docker-compose.yml b/community-plugins/sentiment-meaningCloud/docker-compose.yml
new file mode 100644
index 0000000..8e1c6d1
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/docker-compose.yml
@@ -0,0 +1,28 @@
+version: '3'
+services:
+    dev:
+        image: gsiupm/senpy:latest
+        entrypoint: ["/bin/bash"]
+        working_dir: "/senpy-plugins"
+        tty: true
+        ports:
+            - "127.0.0.1:5005:5000"
+        volumes:
+            - ".:/senpy-plugins"
+    test:
+        image: gsiupm/senpy:latest
+        entrypoint: ["py.test"]
+        working_dir: "/usr/src/app/"
+        volumes:
+            - ".:/senpy-plugins/"
+        command:
+          []
+    meaningcloud:
+        image: "${IMAGENAME-gsiupm/meaningcloud}:${VERSION-dev}"
+        build:
+          context: .
+          dockerfile: Dockerfile-3.5
+        ports:
+            - 5001:5000
+        volumes:
+            - "./data:/data"
diff --git a/community-plugins/sentiment-meaningCloud/k8s/README.md b/community-plugins/sentiment-meaningCloud/k8s/README.md
new file mode 100644
index 0000000..69ca6a1
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/k8s/README.md
@@ -0,0 +1,7 @@
+Deploy senpy to a kubernetes cluster.
+
+Usage:
+
+```
+kubectl apply -f . -n senpy
+```
diff --git a/community-plugins/sentiment-meaningCloud/k8s/senpy-deployment.yaml b/community-plugins/sentiment-meaningCloud/k8s/senpy-deployment.yaml
new file mode 100644
index 0000000..c954f37
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/k8s/senpy-deployment.yaml
@@ -0,0 +1,27 @@
+---
+apiVersion: extensions/v1beta1
+kind: Deployment
+metadata:
+  name: ${NAME}
+spec:
+  replicas: 1
+  template:
+    metadata:
+      labels:
+        role: senpy-plugin
+        app: ${NAME}
+    spec:
+      containers:
+      - name: senpy-latest
+        image: ${CI_REGISTRY_IMAGE}:${VERSION}
+        imagePullPolicy: Always
+        args:
+          - "-f"
+          - "/senpy-plugins"
+        resources:
+          limits:
+            memory: "512Mi"
+            cpu: "1000m"
+        ports:
+          - name: web
+            containerPort: 5000
diff --git a/community-plugins/sentiment-meaningCloud/k8s/senpy-ingress.yaml b/community-plugins/sentiment-meaningCloud/k8s/senpy-ingress.yaml
new file mode 100644
index 0000000..1cb02a6
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/k8s/senpy-ingress.yaml
@@ -0,0 +1,14 @@
+---
+apiVersion: extensions/v1beta1
+kind: Ingress
+metadata:
+  name: ${NAME}
+spec:
+  rules:
+  - host: ${NAME}.senpy.cluster.gsi.dit.upm.es
+    http:
+      paths:
+      - path: /
+        backend:
+          serviceName: ${NAME}
+          servicePort: 5000
diff --git a/community-plugins/sentiment-meaningCloud/k8s/senpy-svc.yaml b/community-plugins/sentiment-meaningCloud/k8s/senpy-svc.yaml
new file mode 100644
index 0000000..cde518c
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/k8s/senpy-svc.yaml
@@ -0,0 +1,12 @@
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: ${NAME}
+spec:
+  type: ClusterIP
+  ports:
+    - port: 5000
+      protocol: TCP
+  selector:
+    app: ${NAME}
diff --git a/community-plugins/sentiment-meaningCloud/meaningcloud_plugin.py b/community-plugins/sentiment-meaningCloud/meaningcloud_plugin.py
new file mode 100644
index 0000000..d3b6213
--- /dev/null
+++ b/community-plugins/sentiment-meaningCloud/meaningcloud_plugin.py
@@ -0,0 +1,254 @@
+# -*- coding: utf-8 -*-
+
+import time
+import requests
+import json
+import string
+import os
+from os import path
+import time
+from senpy.plugins import SentimentPlugin
+from senpy.models import Results, Entry, Entity, Topic, Sentiment, Error
+from senpy.utils import check_template
+
+
+class MeaningCloudPlugin(SentimentPlugin):
+    '''
+    Sentiment analysis with meaningCloud service.
+    To use this plugin, you need to obtain an API key from meaningCloud signing up here:
+    https://www.meaningcloud.com/developer/login
+
+    When you had obtained the meaningCloud API Key, you have to provide it to the plugin, using param apiKey.
+    Example request:
+
+    http://senpy.cluster.gsi.dit.upm.es/api/?algo=meaningCloud&language=en&apiKey=YOUR_API_KEY&input=I%20love%20Madrid.
+    '''
+    name = 'sentiment-meaningcloud'
+    author = 'GSI UPM'
+    version = "1.1"
+    maxPolarityValue = 1
+    minPolarityValue = -1
+
+    extra_params = {
+        "language": {
+            "description": "language of the input",
+            "aliases": ["language", "l"],
+            "required": True,
+            "options": ["en","es","ca","it","pt","fr","auto"],
+            "default": "auto"
+        },
+        "apikey":{
+            "description": "API key for the meaningcloud service. See https://www.meaningcloud.com/developer/login",
+            "aliases": ["apiKey", "meaningcloud-key", "meaningcloud-apikey"],
+            "required": True
+        }
+    }
+
+    def _polarity(self, value):
+
+        if 'NONE' in value:
+            polarity = 'marl:Neutral'
+            polarityValue = 0
+        elif 'N' in value:
+            polarity = 'marl:Negative'
+            polarityValue = -1
+        elif 'P' in value:
+            polarity = 'marl:Positive'
+            polarityValue = 1
+        return polarity, polarityValue
+
+    def analyse_entry(self, entry, activity):
+        params = activity.params
+
+        txt = entry['nif:isString']
+        api = 'http://api.meaningcloud.com/'
+        lang = params.get("language")
+        model = "general"
+        key = params["apikey"]
+        parameters = {
+            'key': key,
+            'model': model,
+            'lang': lang,
+            'of': 'json',
+            'txt': txt,
+            'tt': 'a'
+        }
+        try:
+            r = requests.post(
+                api + "sentiment-2.1", params=parameters, timeout=3)
+            parameters['lang'] = r.json()['model'].split('_')[1]
+            lang = parameters['lang']
+            r2 = requests.post(
+                api + "topics-2.0", params=parameters, timeout=3)
+        except requests.exceptions.Timeout:
+            raise Error("Meaning Cloud API does not response")
+
+        api_response = r.json()
+        api_response_topics = r2.json()
+        if not api_response.get('score_tag'):
+            raise Error(r.json())
+        entry['language_detected'] = lang
+        self.log.debug(api_response)
+        agg_polarity, agg_polarityValue = self._polarity(
+            api_response.get('score_tag', None))
+        agg_opinion = Sentiment(
+            id="Opinion0",
+            marl__hasPolarity=agg_polarity,
+            marl__polarityValue=agg_polarityValue,
+            marl__opinionCount=len(api_response['sentence_list']))
+        agg_opinion.prov(self)
+        entry.sentiments.append(agg_opinion)
+        self.log.debug(api_response['sentence_list'])
+        count = 1
+
+        for sentence in api_response['sentence_list']:
+            for nopinion in sentence['segment_list']:
+                self.log.debug(nopinion)
+                polarity, polarityValue = self._polarity(
+                    nopinion.get('score_tag', None))
+                opinion = Sentiment(
+                    id="Opinion{}".format(count),
+                    marl__hasPolarity=polarity,
+                    marl__polarityValue=polarityValue,
+                    marl__aggregatesOpinion=agg_opinion.get('id'),
+                    nif__anchorOf=nopinion.get('text', None),
+                    nif__beginIndex=int(nopinion.get('inip', None)),
+                    nif__endIndex=int(nopinion.get('endp', None)))
+                count += 1
+                opinion.prov(self)
+                entry.sentiments.append(opinion)
+
+        mapper = {'es': 'es.', 'en': '', 'ca': 'es.', 'it':'it.', 'fr':'fr.', 'pt':'pt.'}
+
+        for sent_entity in api_response_topics['entity_list']:
+            resource = "_".join(sent_entity.get('form', None).split())
+            entity = Entity(
+                id="Entity{}".format(sent_entity.get('id')),
+                itsrdf__taIdentRef="http://{}dbpedia.org/resource/{}".format(
+                    mapper[lang], resource),
+                nif__anchorOf=sent_entity.get('form', None),
+                nif__beginIndex=int(sent_entity['variant_list'][0].get('inip', None)),
+                nif__endIndex=int(sent_entity['variant_list'][0].get('endp', None)))
+            sementity = sent_entity['sementity'].get('type', None).split(">")[-1]
+            entity['@type'] = "ODENTITY_{}".format(sementity)
+            entity.prov(self)
+            if 'senpy:hasEntity' not in entry:
+                entry['senpy:hasEntity'] = []
+            entry['senpy:hasEntity'].append(entity)
+
+        for topic in api_response_topics['concept_list']:
+            if 'semtheme_list' in topic:
+                for theme in topic['semtheme_list']:
+                    concept = Topic()
+                    concept.id = "Topic{}".format(topic.get('id'))
+                    concept['@type'] = "ODTHEME_{}".format(theme['type'].split(">")[-1])
+                    concept['fam:topic-reference'] = "http://dbpedia.org/resource/{}".format(theme['type'].split('>')[-1])
+                    entry.prov(self)
+                    if 'senpy:hasTopic' not in entry:
+                        entry['senpy:hasTopic'] = []
+                    entry['senpy:hasTopic'].append(concept)
+        yield entry
+
+    test_cases = [
+        {
+            'params': {
+                'algo': 'sentiment-meaningCloud',
+                'intype': 'direct',
+                'expanded-jsonld': 0,
+                'informat': 'text',
+                'prefix': '',
+                'plugin_type': 'analysisPlugin',
+                'urischeme': 'RFC5147String',
+                'outformat': 'json-ld',
+                'conversion': 'full',
+                'language': 'en',
+                'apikey': '00000',
+                'algorithm': 'sentiment-meaningCloud'
+            },
+            'input': 'Hello World Obama',
+            'expected': {
+                'marl:hasOpinion': [
+                    {'marl:hasPolarity': 'marl:Neutral'}],
+                'senpy:hasEntity': [
+                    {'itsrdf:taIdentRef': 'http://dbpedia.org/resource/Obama'}],
+                'senpy:hasTopic': [
+                    {'fam:topic-reference': 'http://dbpedia.org/resource/Astronomy'}]
+            },
+            'responses': [
+                {
+                    'url':  'http://api.meaningcloud.com/sentiment-2.1',
+                    'method': 'POST',
+                    'json': {
+                        'model': 'general_en',
+                        'sentence_list': [{
+                            'text':
+                            'Hello World',
+                            'endp':
+                            '10',
+                            'inip':
+                            '0',
+                            'segment_list': [{
+                                'text':
+                                'Hello World',
+                                'segment_type':
+                                'secondary',
+                                'confidence':
+                                '100',
+                                'inip':
+                                '0',
+                                'agreement':
+                                'AGREEMENT',
+                                'endp':
+                                '10',
+                                'polarity_term_list': [],
+                                'score_tag':
+                                'NONE'
+                            }],
+                            'score_tag':
+                            'NONE',
+                        }],
+                        'score_tag':
+                        'NONE'
+                    }
+                }, {
+                    'url':  'http://api.meaningcloud.com/topics-2.0',
+                    'method': 'POST',
+                    'json': {
+                        'entity_list': [{
+                            'form':
+                            'Obama',
+                            'id':
+                            '__1265958475430276310',
+                            'variant_list': [{
+                                'endp': '16',
+                                'form': 'Obama',
+                                'inip': '12'
+                            }],
+                            'sementity': {
+                                'fiction': 'nonfiction',
+                                'confidence': 'uncertain',
+                                'class': 'instance',
+                                'type': 'Top>Person'
+                            }
+                        }],
+                        'concept_list': [{
+                            'form':
+                            'world',
+                            'id':
+                            '5c053cd39d',
+                            'relevance':
+                            '100',
+                            'semtheme_list': [{
+                                'id': 'ODTHEME_ASTRONOMY',
+                                'type': 'Top>NaturalSciences>Astronomy'
+                            }]
+                        }],
+                    }
+                }]
+        }
+    ]
+
+
+if __name__ == '__main__':
+    from senpy import easy_test
+    easy_test()
diff --git a/community-plugins/sentiment-senticnet/senticnet_plugin.py b/community-plugins/sentiment-senticnet/senticnet_plugin.py
new file mode 100644
index 0000000..200634a
--- /dev/null
+++ b/community-plugins/sentiment-senticnet/senticnet_plugin.py
@@ -0,0 +1,87 @@
+#
+#    Copyright 2014 Grupo de Sistemas Inteligentes (GSI) DIT, UPM
+#
+#    Licensed under the Apache License, Version 2.0 (the "License");
+#    you may not use this file except in compliance with the License.
+#    You may obtain a copy of the License at
+#
+#        http://www.apache.org/licenses/LICENSE-2.0
+#
+#    Unless required by applicable law or agreed to in writing, software
+#    distributed under the License is distributed on an "AS IS" BASIS,
+#    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#    See the License for the specific language governing permissions and
+#    limitations under the License.
+#
+
+import requests
+import json
+
+from senpy.plugins import SentimentBox
+from senpy import easy_test
+
+ENDPOINT = 'http://sentiment.gelbukh.com/sentiment/run.php'
+
+
+class Senticnet(SentimentBox):
+    '''Connects to the SenticNet free polarity detection API: http://sentiment.gelbukh.com/sentiment/'''
+
+    author = "@balkian"
+    version = '0.1'
+    url = "https://github.com/gsi-upm/senpy-plugins-community"
+    extra_params = {
+    }
+
+    classes = ['marl:Positive', 'marl:Neutral', 'marl:Negative']
+    binary = True
+
+    def predict_one(self, features, activity):
+        text = ' '.join(features)
+
+        res = requests.post(ENDPOINT,
+                            data={'input':  text})
+
+        if '-' not in res.text:
+            raise Exception('Invalid response from server: {}'.format(res.text))
+
+        label = res.text.split('-')[1].lower()
+
+        if 'positive' in label:
+            return [1, 0, 0]
+        elif 'negative' in label:
+            return [0, 0, 1]
+
+        return [0, 1, 0]
+
+    test_cases = [
+        {
+            'entry': {
+                'nif:isString': 'I love Titanic'
+            },
+            'params': {},
+            'expected': {
+                "nif:isString": "I love Titanic",
+                'marl:hasOpinion': [
+                    {
+                        'marl:hasPolarity': 'marl:Positive',
+                    }
+                ]
+            },
+        }, {
+            'entry': {
+                'nif:isString': 'I hate my life'
+            },
+            'params': {},
+            'expected': {
+                "nif:isString": "I hate my life",
+                'marl:hasOpinion': [
+                    {
+                        'marl:hasPolarity': 'marl:Negative',
+                    }
+                ]
+            },
+        }, 
+    ]
+
+if __name__ == '__main__':
+    easy_test()
diff --git a/community-plugins/sentiment-vader/README.md b/community-plugins/sentiment-vader/README.md
new file mode 100644
index 0000000..e47109a
--- /dev/null
+++ b/community-plugins/sentiment-vader/README.md
@@ -0,0 +1,42 @@
+# Sentimet-vader plugin
+
+Vader is a plugin developed at GSI UPM for sentiment analysis.  
+The response of this plugin uses [Marl ontology](https://www.gsi.dit.upm.es/ontologies/marl/) developed at GSI UPM for semantic web.
+
+## Acknowledgements
+
+This plugin uses the vaderSentiment module underneath, which is described in the paper:
+
+  VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text
+  C.J. Hutto and Eric Gilbert
+  Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.
+
+If you use this plugin in your research, please cite the above paper.
+
+For more information about the functionality, check the official repository
+
+https://github.com/cjhutto/vaderSentiment
+
+## Usage
+
+Parameters:
+
+- Language: es (Spanish), en(English).
+- Input: Text to analyse.
+
+
+Example request: 
+
+```
+http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-vader&language=en&input=I%20love%20Madrid
+```
+
+Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section. 
+
+This plugin supports **python3**
+
+![alt GSI Logo][logoGSI]
+
+[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
+
+========
diff --git a/community-plugins/sentiment-vader/vaderSentiment.py b/community-plugins/sentiment-vader/vaderSentiment.py
new file mode 100644
index 0000000..31825a6
--- /dev/null
+++ b/community-plugins/sentiment-vader/vaderSentiment.py
@@ -0,0 +1,368 @@
+#!/usr/bin/python
+# coding: utf-8 
+'''
+Created on July 04, 2013
+@author: C.J. Hutto
+
+Citation Information
+
+If you use any of the VADER sentiment analysis tools 
+(VADER sentiment lexicon or Python code for rule-based sentiment 
+analysis engine) in your work or research, please cite the paper. 
+For example:
+
+  Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for 
+  Sentiment Analysis of Social Media Text. Eighth International Conference on 
+  Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.
+'''
+
+import os, math, re, sys, fnmatch, string 
+import codecs
+
+def make_lex_dict(f):
+    maps = {}
+    with codecs.open(f, encoding='iso-8859-1') as f:
+        for wmsr in f:
+            w, m = wmsr.strip().split('\t')[:2]
+            maps[w] = m
+    return maps
+    
+f = 'vader_sentiment_lexicon.txt' # empirically derived valence ratings for words, emoticons, slang, swear words, acronyms/initialisms
+try:
+    word_valence_dict = make_lex_dict(f)
+except:
+    f = os.path.join(os.path.dirname(__file__),'vader_sentiment_lexicon.txt')
+    word_valence_dict = make_lex_dict(f)
+
+# for removing punctuation
+regex_remove_punctuation = re.compile('[%s]' % re.escape(string.punctuation))
+
+def sentiment(text):
+    """
+    Returns a float for sentiment strength based on the input text.
+    Positive values are positive valence, negative value are negative valence.
+    """
+    wordsAndEmoticons = str(text).split() #doesn't separate words from adjacent punctuation (keeps emoticons & contractions)
+    text_mod = regex_remove_punctuation.sub('', text) # removes punctuation (but loses emoticons & contractions)
+    wordsOnly = str(text_mod).split()
+    # get rid of empty items or single letter "words" like 'a' and 'I' from wordsOnly
+    for word in wordsOnly:
+        if len(word) <= 1:
+            wordsOnly.remove(word)    
+    # now remove adjacent & redundant punctuation from [wordsAndEmoticons] while keeping emoticons and contractions
+    puncList = [".", "!", "?", ",", ";", ":", "-", "'", "\"", 
+                "!!", "!!!", "??", "???", "?!?", "!?!", "?!?!", "!?!?"] 
+    for word in wordsOnly:
+        for p in puncList:
+            pword = p + word
+            x1 = wordsAndEmoticons.count(pword)
+            while x1 > 0:
+                i = wordsAndEmoticons.index(pword)
+                wordsAndEmoticons.remove(pword)
+                wordsAndEmoticons.insert(i, word)
+                x1 = wordsAndEmoticons.count(pword)
+            
+            wordp = word + p
+            x2 = wordsAndEmoticons.count(wordp)
+            while x2 > 0:
+                i = wordsAndEmoticons.index(wordp)
+                wordsAndEmoticons.remove(wordp)
+                wordsAndEmoticons.insert(i, word)
+                x2 = wordsAndEmoticons.count(wordp)
+    # get rid of residual empty items or single letter "words" like 'a' and 'I' from wordsAndEmoticons
+    for word in wordsAndEmoticons:
+        if len(word) <= 1:
+            wordsAndEmoticons.remove(word)
+    
+    # remove stopwords from [wordsAndEmoticons]
+    #stopwords = [str(word).strip() for word in open('stopwords.txt')]
+    #for word in wordsAndEmoticons:
+    #    if word in stopwords:
+    #        wordsAndEmoticons.remove(word)
+    
+    # check for negation
+    negate = ["aint", "arent", "cannot", "cant", "couldnt", "darent", "didnt", "doesnt",
+              "ain't", "aren't", "can't", "couldn't", "daren't", "didn't", "doesn't",
+              "dont", "hadnt", "hasnt", "havent", "isnt", "mightnt", "mustnt", "neither",
+              "don't", "hadn't", "hasn't", "haven't", "isn't", "mightn't", "mustn't",
+              "neednt", "needn't", "never", "none", "nope", "nor", "not", "nothing", "nowhere", 
+              "oughtnt", "shant", "shouldnt", "uhuh", "wasnt", "werent",
+              "oughtn't", "shan't", "shouldn't", "uh-uh", "wasn't", "weren't",  
+              "without", "wont", "wouldnt", "won't", "wouldn't", "rarely", "seldom", "despite"]
+    def negated(list, nWords=[], includeNT=True):
+        nWords.extend(negate)
+        for word in nWords:
+            if word in list:
+                return True
+        if includeNT:
+            for word in list:
+                if "n't" in word:
+                    return True
+        if "least" in list:
+            i = list.index("least")
+            if i > 0 and list[i-1] != "at":
+                return True
+        return False
+        
+    def normalize(score, alpha=15):
+        # normalize the score to be between -1 and 1 using an alpha that approximates the max expected value 
+        normScore = score/math.sqrt( ((score*score) + alpha) )
+        return normScore
+    
+    def wildCardMatch(patternWithWildcard, listOfStringsToMatchAgainst):
+        listOfMatches = fnmatch.filter(listOfStringsToMatchAgainst, patternWithWildcard)
+        return listOfMatches
+        
+    
+    def isALLCAP_differential(wordList):
+        countALLCAPS= 0
+        for w in wordList:
+            if str(w).isupper(): 
+                countALLCAPS += 1
+        cap_differential = len(wordList) - countALLCAPS
+        if cap_differential > 0 and cap_differential < len(wordList):
+            isDiff = True
+        else: isDiff = False
+        return isDiff
+    isCap_diff = isALLCAP_differential(wordsAndEmoticons)
+    
+    b_incr = 0.293 #(empirically derived mean sentiment intensity rating increase for booster words)
+    b_decr = -0.293
+    # booster/dampener 'intensifiers' or 'degree adverbs' http://en.wiktionary.org/wiki/Category:English_degree_adverbs
+    booster_dict = {"absolutely": b_incr, "amazingly": b_incr, "awfully": b_incr, "completely": b_incr, "considerably": b_incr, 
+                    "decidedly": b_incr, "deeply": b_incr, "effing": b_incr, "enormously": b_incr, 
+                    "entirely": b_incr, "especially": b_incr, "exceptionally": b_incr, "extremely": b_incr,
+                    "fabulously": b_incr, "flipping": b_incr, "flippin": b_incr, 
+                    "fricking": b_incr, "frickin": b_incr, "frigging": b_incr, "friggin": b_incr, "fully": b_incr, "fucking": b_incr, 
+                    "greatly": b_incr, "hella": b_incr, "highly": b_incr, "hugely": b_incr, "incredibly": b_incr, 
+                    "intensely": b_incr, "majorly": b_incr, "more": b_incr, "most": b_incr, "particularly": b_incr, 
+                    "purely": b_incr, "quite": b_incr, "really": b_incr, "remarkably": b_incr, 
+                    "so": b_incr,  "substantially": b_incr, 
+                    "thoroughly": b_incr, "totally": b_incr, "tremendously": b_incr, 
+                    "uber": b_incr, "unbelievably": b_incr, "unusually": b_incr, "utterly": b_incr, 
+                    "very": b_incr, 
+                    
+                    "almost": b_decr, "barely": b_decr, "hardly": b_decr, "just enough": b_decr, 
+                    "kind of": b_decr, "kinda": b_decr, "kindof": b_decr, "kind-of": b_decr,
+                    "less": b_decr, "little": b_decr, "marginally": b_decr, "occasionally": b_decr, "partly": b_decr, 
+                    "scarcely": b_decr, "slightly": b_decr, "somewhat": b_decr, 
+                    "sort of": b_decr, "sorta": b_decr, "sortof": b_decr, "sort-of": b_decr}
+    sentiments = []
+    for item in wordsAndEmoticons:
+        v = 0
+        i = wordsAndEmoticons.index(item)
+        if (i < len(wordsAndEmoticons)-1 and str(item).lower() == "kind" and \
+           str(wordsAndEmoticons[i+1]).lower() == "of") or str(item).lower() in booster_dict:
+            sentiments.append(v)
+            continue
+        item_lowercase = str(item).lower() 
+        if  item_lowercase in word_valence_dict:
+            #get the sentiment valence
+            v = float(word_valence_dict[item_lowercase])
+            
+            #check if sentiment laden word is in ALLCAPS (while others aren't)
+            c_incr = 0.733 #(empirically derived mean sentiment intensity rating increase for using ALLCAPs to emphasize a word)
+            if str(item).isupper() and isCap_diff:
+                if v > 0: v += c_incr
+                else: v -= c_incr
+            
+            #check if the preceding words increase, decrease, or negate/nullify the valence
+            def scalar_inc_dec(word, valence):
+                scalar = 0.0
+                word_lower = str(word).lower()
+                if word_lower in booster_dict:
+                    scalar = booster_dict[word_lower]
+                    if valence < 0: scalar *= -1
+                    #check if booster/dampener word is in ALLCAPS (while others aren't)
+                    if str(word).isupper() and isCap_diff:
+                        if valence > 0: scalar += c_incr
+                        else:  scalar -= c_incr
+                return scalar
+            n_scalar = -0.74
+            if i > 0 and str(wordsAndEmoticons[i-1]).lower() not in word_valence_dict:
+                s1 = scalar_inc_dec(wordsAndEmoticons[i-1], v)
+                v = v+s1
+                if negated([wordsAndEmoticons[i-1]]): v = v*n_scalar
+            if i > 1 and str(wordsAndEmoticons[i-2]).lower() not in word_valence_dict:
+                s2 = scalar_inc_dec(wordsAndEmoticons[i-2], v)
+                if s2 != 0: s2 = s2*0.95
+                v = v+s2
+                # check for special use of 'never' as valence modifier instead of negation
+                if wordsAndEmoticons[i-2] == "never" and (wordsAndEmoticons[i-1] == "so" or wordsAndEmoticons[i-1] == "this"): 
+                    v = v*1.5                    
+                # otherwise, check for negation/nullification
+                elif negated([wordsAndEmoticons[i-2]]): v = v*n_scalar
+            if i > 2 and str(wordsAndEmoticons[i-3]).lower() not in word_valence_dict:
+                s3 = scalar_inc_dec(wordsAndEmoticons[i-3], v)
+                if s3 != 0: s3 = s3*0.9
+                v = v+s3
+                # check for special use of 'never' as valence modifier instead of negation
+                if wordsAndEmoticons[i-3] == "never" and \
+                   (wordsAndEmoticons[i-2] == "so" or wordsAndEmoticons[i-2] == "this") or \
+                   (wordsAndEmoticons[i-1] == "so" or wordsAndEmoticons[i-1] == "this"):
+                    v = v*1.25
+                # otherwise, check for negation/nullification
+                elif negated([wordsAndEmoticons[i-3]]): v = v*n_scalar
+                
+                # check for special case idioms using a sentiment-laden keyword known to SAGE
+                special_case_idioms = {"the shit": 3, "the bomb": 3, "bad ass": 1.5, "yeah right": -2, 
+                                       "cut the mustard": 2, "kiss of death": -1.5, "hand to mouth": -2}
+                # future work: consider other sentiment-laden idioms
+                #other_idioms = {"back handed": -2, "blow smoke": -2, "blowing smoke": -2, "upper hand": 1, "break a leg": 2, 
+                #                "cooking with gas": 2, "in the black": 2, "in the red": -2, "on the ball": 2,"under the weather": -2}
+                onezero = "{} {}".format(str(wordsAndEmoticons[i-1]), str(wordsAndEmoticons[i]))
+                twoonezero = "{} {} {}".format(str(wordsAndEmoticons[i-2]), str(wordsAndEmoticons[i-1]), str(wordsAndEmoticons[i]))
+                twoone = "{} {}".format(str(wordsAndEmoticons[i-2]), str(wordsAndEmoticons[i-1]))
+                threetwoone = "{} {} {}".format(str(wordsAndEmoticons[i-3]), str(wordsAndEmoticons[i-2]), str(wordsAndEmoticons[i-1]))
+                threetwo = "{} {}".format(str(wordsAndEmoticons[i-3]), str(wordsAndEmoticons[i-2]))                    
+                if onezero in special_case_idioms: v = special_case_idioms[onezero]
+                elif twoonezero in special_case_idioms: v = special_case_idioms[twoonezero]
+                elif twoone in special_case_idioms: v = special_case_idioms[twoone]
+                elif threetwoone in special_case_idioms: v = special_case_idioms[threetwoone]
+                elif threetwo in special_case_idioms: v = special_case_idioms[threetwo]
+                if len(wordsAndEmoticons)-1 > i:
+                    zeroone = "{} {}".format(str(wordsAndEmoticons[i]), str(wordsAndEmoticons[i+1]))
+                    if zeroone in special_case_idioms: v = special_case_idioms[zeroone]
+                if len(wordsAndEmoticons)-1 > i+1:
+                    zeroonetwo = "{} {}".format(str(wordsAndEmoticons[i]), str(wordsAndEmoticons[i+1]), str(wordsAndEmoticons[i+2]))
+                    if zeroonetwo in special_case_idioms: v = special_case_idioms[zeroonetwo]
+                
+                # check for booster/dampener bi-grams such as 'sort of' or 'kind of'
+                if threetwo in booster_dict or twoone in booster_dict:
+                    v = v+b_decr
+            
+            # check for negation case using "least"
+            if i > 1 and str(wordsAndEmoticons[i-1]).lower() not in word_valence_dict \
+                and str(wordsAndEmoticons[i-1]).lower() == "least":
+                if (str(wordsAndEmoticons[i-2]).lower() != "at" and str(wordsAndEmoticons[i-2]).lower() != "very"):
+                    v = v*n_scalar
+            elif i > 0 and str(wordsAndEmoticons[i-1]).lower() not in word_valence_dict \
+                and str(wordsAndEmoticons[i-1]).lower() == "least":
+                v = v*n_scalar
+        sentiments.append(v) 
+            
+    # check for modification in sentiment due to contrastive conjunction 'but'
+    if 'but' in wordsAndEmoticons or 'BUT' in wordsAndEmoticons:
+        try: bi = wordsAndEmoticons.index('but')
+        except: bi = wordsAndEmoticons.index('BUT')
+        for s in sentiments:
+            si = sentiments.index(s)
+            if si < bi: 
+                sentiments.pop(si)
+                sentiments.insert(si, s*0.5)
+            elif si > bi: 
+                sentiments.pop(si)
+                sentiments.insert(si, s*1.5) 
+                
+    if sentiments:                      
+        sum_s = float(sum(sentiments))
+        #print sentiments, sum_s
+        
+        # check for added emphasis resulting from exclamation points (up to 4 of them)
+        ep_count = str(text).count("!")
+        if ep_count > 4: ep_count = 4
+        ep_amplifier = ep_count*0.292 #(empirically derived mean sentiment intensity rating increase for exclamation points)
+        if sum_s > 0:  sum_s += ep_amplifier
+        elif  sum_s < 0: sum_s -= ep_amplifier
+        
+        # check for added emphasis resulting from question marks (2 or 3+)
+        qm_count = str(text).count("?")
+        qm_amplifier = 0
+        if qm_count > 1:
+            if qm_count <= 3: qm_amplifier = qm_count*0.18
+            else: qm_amplifier = 0.96
+            if sum_s > 0:  sum_s += qm_amplifier
+            elif  sum_s < 0: sum_s -= qm_amplifier
+
+        compound = normalize(sum_s)
+        
+        # want separate positive versus negative sentiment scores
+        pos_sum = 0.0
+        neg_sum = 0.0
+        neu_count = 0
+        for sentiment_score in sentiments:
+            if sentiment_score > 0:
+                pos_sum += (float(sentiment_score) +1) # compensates for neutral words that are counted as 1
+            if sentiment_score < 0:
+                neg_sum += (float(sentiment_score) -1) # when used with math.fabs(), compensates for neutrals
+            if sentiment_score == 0:
+                neu_count += 1
+        
+        if pos_sum > math.fabs(neg_sum): pos_sum += (ep_amplifier+qm_amplifier)
+        elif pos_sum < math.fabs(neg_sum): neg_sum -= (ep_amplifier+qm_amplifier)
+        
+        total = pos_sum + math.fabs(neg_sum) + neu_count
+        pos = math.fabs(pos_sum / total)
+        neg = math.fabs(neg_sum / total)
+        neu = math.fabs(neu_count / total)
+        
+    else:
+        compound = 0.0; pos = 0.0; neg = 0.0; neu = 0.0
+        
+    s = {"neg" : round(neg, 3), 
+         "neu" : round(neu, 3),
+         "pos" : round(pos, 3),
+         "compound" : round(compound, 4)}
+    return s
+
+
+if __name__ == '__main__':
+    # --- examples -------
+    sentences = [
+                "VADER is smart, handsome, and funny.",       # positive sentence example
+                "VADER is smart, handsome, and funny!",       # punctuation emphasis handled correctly (sentiment intensity adjusted)
+                "VADER is very smart, handsome, and funny.",  # booster words handled correctly (sentiment intensity adjusted)
+                "VADER is VERY SMART, handsome, and FUNNY.",  # emphasis for ALLCAPS handled
+                "VADER is VERY SMART, handsome, and FUNNY!!!",# combination of signals - VADER appropriately adjusts intensity
+                "VADER is VERY SMART, really handsome, and INCREDIBLY FUNNY!!!",# booster words & punctuation make this close to ceiling for score
+                "The book was good.",         # positive sentence
+                "The book was kind of good.", # qualified positive sentence is handled correctly (intensity adjusted)
+                "The plot was good, but the characters are uncompelling and the dialog is not great.", # mixed negation sentence
+                "A really bad, horrible book.",       # negative sentence with booster words
+                "At least it isn't a horrible book.", # negated negative sentence with contraction
+                ":) and :D",     # emoticons handled
+                "",              # an empty string is correctly handled
+                "Today sux",     #  negative slang handled
+                "Today sux!",    #  negative slang with punctuation emphasis handled
+                "Today SUX!",    #  negative slang with capitalization emphasis
+                "Today kinda sux! But I'll get by, lol" # mixed sentiment example with slang and constrastive conjunction "but"
+                 ]
+    paragraph = "It was one of the worst movies I've seen, despite good reviews. \
+    Unbelievably bad acting!! Poor direction. VERY poor production. \
+    The movie was bad. Very bad movie. VERY bad movie. VERY BAD movie. VERY BAD movie!"
+    
+    from nltk import tokenize
+    lines_list = tokenize.sent_tokenize(paragraph)
+    sentences.extend(lines_list)
+    
+    tricky_sentences = [
+                        "Most automated sentiment analysis tools are shit.",
+                        "VADER sentiment analysis is the shit.",
+                        "Sentiment analysis has never been good.",
+                        "Sentiment analysis with VADER has never been this good.",
+                        "Warren Beatty has never been so entertaining.",
+                        "I won't say that the movie is astounding and I wouldn't claim that the movie is too banal either.",
+                        "I like to hate Michael Bay films, but I couldn't fault this one",
+                        "It's one thing to watch an Uwe Boll film, but another thing entirely to pay for it",
+                        "The movie was too good",
+                        "This movie was actually neither that funny, nor super witty.",
+                        "This movie doesn't care about cleverness, wit or any other kind of intelligent humor.",
+                        "Those who find ugly meanings in beautiful things are corrupt without being charming.",
+                        "There are slow and repetitive parts, BUT it has just enough spice to keep it interesting.",
+                        "The script is not fantastic, but the acting is decent and the cinematography is EXCELLENT!", 
+                        "Roger Dodger is one of the most compelling variations on this theme.",
+                        "Roger Dodger is one of the least compelling variations on this theme.",
+                        "Roger Dodger is at least compelling as a variation on the theme.",
+                        "they fall in love with the product",
+                        "but then it breaks",
+                        "usually around the time the 90 day warranty expires",
+                        "the twin towers collapsed today",
+                        "However, Mr. Carter solemnly argues, his client carried out the kidnapping under orders and in the ''least offensive way possible.''"
+                        ]
+    sentences.extend(tricky_sentences)
+    for sentence in sentences:
+        print(sentence)
+        ss = sentiment(sentence)
+        print("\t" + str(ss))
+    
+    print("\n\n Done!")
diff --git a/community-plugins/sentiment-vader/vader_plugin.py b/community-plugins/sentiment-vader/vader_plugin.py
new file mode 100644
index 0000000..3b06f0c
--- /dev/null
+++ b/community-plugins/sentiment-vader/vader_plugin.py
@@ -0,0 +1,74 @@
+# -*- coding: utf-8 -*-
+
+from vaderSentiment import sentiment
+from senpy.plugins import SentimentBox, SenpyPlugin
+from senpy.models import Results, Sentiment, Entry
+import logging
+
+
+class VaderSentimentPlugin(SentimentBox):
+    '''
+    Sentiment classifier using vaderSentiment module. Params accepted: Language: {en, es}. The output uses Marl ontology developed at GSI UPM for semantic web.
+    '''
+    name = "sentiment-vader"
+    module = "sentiment-vader"
+    author = "@icorcuera"
+    version = "0.1.1"
+    extra_params = {
+        "language": {
+          "description": "language of the input",
+          "@id": "lang_rand",
+          "aliases": ["language", "l"],
+          "default": "auto",
+          "options": ["es", "en", "auto"]
+        },
+
+        "aggregate": {
+            "description": "Show only the strongest sentiment (aggregate) or all sentiments",
+            "aliases": ["aggregate","agg"],
+            "options": [True, False],
+            "default": False
+        }
+
+    }
+    requirements = {}
+
+    _VADER_KEYS = ['pos', 'neu', 'neg']
+    binary = False
+
+
+    def predict_one(self, features, activity):
+        text_input = ' '.join(features)
+        scores = sentiment(text_input)
+
+        sentiments = []
+        for k in self._VADER_KEYS:
+            sentiments.append(scores[k])
+
+        if activity.param('aggregate'):
+            m = max(sentiments)
+            sentiments = [k if k==m else None for k in sentiments]
+
+        return sentiments
+
+    test_cases = []
+
+    test_cases = [
+        {
+            'input': 'I am tired :(',
+            'polarity': 'marl:Negative'
+        },
+        {
+            'input': 'I love pizza :(',
+            'polarity': 'marl:Positive'
+        },
+        {
+            'input': 'I enjoy going to the cinema :)',
+            'polarity': 'marl:Negative'
+        },
+        {
+            'input': 'This cake is disgusting',
+            'polarity': 'marl:Negative'
+        },
+        
+    ]
diff --git a/community-plugins/sentiment-vader/vader_sentiment_lexicon.txt b/community-plugins/sentiment-vader/vader_sentiment_lexicon.txt
new file mode 100644
index 0000000..dba1012
--- /dev/null
+++ b/community-plugins/sentiment-vader/vader_sentiment_lexicon.txt
@@ -0,0 +1,7517 @@
+$:	-1.5	0.80623	[-1, -1, -1, -1, -3, -1, -3, -1, -2, -1]
+%)	-0.4	1.0198	[-1, 0, -1, 0, 0, -2, -1, 2, -1, 0]
+%-)	-1.5	1.43178	[-2, 0, -2, -2, -1, 2, -2, -3, -2, -3]
+&-:	-0.4	1.42829	[-3, -1, 0, 0, -1, -1, -1, 2, -1, 2]
+&:	-0.7	0.64031	[0, -1, -1, -1, 1, -1, -1, -1, -1, -1]
+( '}{' )	1.6	0.66332	[1, 2, 2, 1, 1, 2, 2, 1, 3, 1]
+(%	-0.9	0.9434	[0, 0, 1, -1, -1, -1, -2, -2, -1, -2]
+('-:	2.2	1.16619	[4, 1, 4, 3, 1, 2, 3, 1, 2, 1]
+(':	2.3	0.9	[1, 3, 3, 2, 2, 4, 2, 3, 1, 2]
+((-:	2.1	0.53852	[2, 2, 2, 1, 2, 3, 2, 2, 3, 2]
+(*	1.1	1.13578	[2, 1, 1, -1, 1, 2, 2, -1, 2, 2]
+(-%	-0.7	1.26886	[-1, 2, 0, -1, -1, -2, 0, 0, -3, -1]
+(-*	1.3	1.26886	[4, 1, 2, 0, 2, -1, 1, 2, 1, 1]
+(-:	1.6	0.8	[2, 2, 1, 3, 1, 1, 1, 3, 1, 1]
+(-:0	2.8	0.87178	[3, 2, 3, 4, 3, 2, 3, 1, 4, 3]
+(-:<	-0.4	2.15407	[-3, 3, -1, -1, 2, -1, -2, 3, -3, -1]
+(-:o	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
+(-:O	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
+(-:{	-0.1	1.57797	[-2, -3, 1, -2, 1, 1, 0, 0, 2, 1]
+(-:|>*	1.9	0.83066	[3, 2, 2, 1, 0, 2, 3, 2, 2, 2]
+(-;	1.3	1.18743	[3, 2, 3, 0, 1, -1, 1, 2, 1, 1]
+(-;|	2.1	1.13578	[3, 2, 2, 4, 1, 1, 1, 4, 2, 1]
+(8	2.6	1.0198	[4, 2, 1, 3, 3, 3, 3, 1, 2, 4]
+(:	2.2	1.16619	[3, 1, 1, 2, 1, 2, 4, 3, 4, 1]
+(:0	2.4	1.11355	[0, 2, 3, 4, 3, 2, 3, 3, 1, 3]
+(:<	-0.2	2.03961	[-2, -3, 1, 1, 2, -1, 2, 1, -4, 1]
+(:o	2.5	0.92195	[3, 3, 1, 3, 3, 1, 2, 2, 4, 3]
+(:O	2.5	0.92195	[3, 3, 1, 3, 3, 1, 2, 2, 4, 3]
+(;	1.1	1.22066	[3, 1, 1, -1, 1, 2, 2, -1, 1, 2]
+(;<	0.3	1.00499	[1, 2, -1, -1, 0, 0, 1, -1, 1, 1]
+(=	2.2	1.16619	[3, 1, 2, 2, 1, 1, 4, 3, 4, 1]
+(?:	2.1	0.83066	[2, 2, 1, 3, 2, 2, 4, 1, 2, 2]
+(^:	1.5	0.67082	[1, 2, 2, 1, 3, 2, 1, 1, 1, 1]
+(^;	1.5	0.5	[1, 2, 2, 1, 2, 1, 2, 1, 1, 2]
+(^;0	2.0	0.7746	[2, 2, 1, 2, 1, 4, 2, 2, 2, 2]
+(^;o	1.9	0.83066	[2, 2, 1, 2, 1, 4, 2, 1, 2, 2]
+(o:	1.6	0.8	[2, 1, 3, 1, 1, 1, 2, 3, 1, 1]
+)':	-2.0	0.44721	[-2, -2, -2, -2, -1, -3, -2, -2, -2, -2]
+)-':	-2.1	0.53852	[-2, -2, -3, -2, -1, -2, -3, -2, -2, -2]
+)-:	-2.1	0.9434	[-3, -2, -4, -1, -3, -2, -2, -2, -1, -1]
+)-:<	-2.2	0.4	[-2, -2, -2, -2, -2, -2, -3, -3, -2, -2]
+)-:{	-2.1	0.9434	[-1, -3, -2, -1, -2, -2, -3, -4, -1, -2]
+):	-1.8	0.87178	[-1, -3, -1, -2, -1, -3, -1, -3, -1, -2]
+):<	-1.9	0.53852	[-1, -3, -2, -2, -2, -1, -2, -2, -2, -2]
+):{	-2.3	0.78102	[-1, -2, -3, -3, -2, -2, -4, -2, -2, -2]
+);<	-2.6	0.8	[-2, -2, -2, -3, -2, -3, -2, -2, -4, -4]
+*)	0.6	1.42829	[1, -1, 1, -3, 1, 1, 2, 1, 1, 2]
+*-)	0.3	1.61555	[1, -3, -2, 2, 1, 1, -1, 2, 1, 1]
+*-:	2.1	1.51327	[2, 2, 4, 4, 2, 1, -1, 4, 1, 2]
+*-;	2.4	1.62481	[2, 3, 4, 4, 2, 1, -1, 4, 1, 4]
+*:	1.9	1.04403	[2, 1, 1, 3, 1, 2, 4, 3, 1, 1]
+*<|:-)	1.6	1.28062	[0, 1, 3, 1, 1, 2, 3, 0, 4, 1]
+*\0/*	2.3	1.00499	[2, 0, 3, 1, 3, 3, 2, 3, 3, 3]
+*^:	1.6	1.42829	[2, 2, 1, 3, 2, 2, 3, 3, -1, -1]
+,-:	1.2	0.4	[1, 1, 2, 1, 1, 1, 1, 1, 2, 1]
+---'-;-{@	2.3	1.18743	[0, 1, 3, 4, 2, 3, 2, 2, 2, 4]
+--<--<@	2.2	1.249	[0, 1, 2, 4, 2, 1, 3, 2, 3, 4]
+.-:	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -2, -1]
+..###-:	-1.7	0.78102	[-2, -3, -3, -2, -1, -1, -1, -1, -1, -2]
+..###:	-1.9	1.04403	[-4, -1, -3, -1, -2, -2, -1, -3, -1, -1]
+/-:	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -1, -2, -3, -1]
+/:	-1.3	0.45826	[-2, -1, -1, -1, -2, -1, -1, -2, -1, -1]
+/:<	-1.4	0.4899	[-1, -2, -2, -1, -1, -1, -1, -1, -2, -2]
+/=	-0.9	0.53852	[-1, -1, -1, 0, -1, -2, -1, -1, -1, 0]
+/^:	-1.0	0.7746	[-2, -1, -2, 1, -1, -1, -1, -1, -1, -1]
+/o:	-1.4	0.66332	[0, -2, -1, -1, -2, -2, -1, -2, -1, -2]
+0-8	0.1	1.44568	[2, -1, -2, 0, 2, 0, 2, 0, -2, 0]
+0-|	-1.2	0.4	[-2, -1, -1, -1, -1, -1, -1, -1, -2, -1]
+0:)	1.9	1.04403	[2, 2, 2, 1, 0, 2, 4, 1, 3, 2]
+0:-)	1.4	0.91652	[2, 1, 0, 1, 2, 3, 2, 1, 2, 0]
+0:-3	1.5	0.92195	[2, 1, 0, 2, 2, 3, 2, 1, 2, 0]
+0:03	1.9	1.22066	[2, 3, 2, 0, 0, 1, 4, 2, 3, 2]
+0;^)	1.6	0.91652	[0, 1, 3, 1, 2, 1, 2, 1, 2, 3]
+0_o	-0.3	0.78102	[0, -2, 0, 1, 0, 0, -1, 0, -1, 0]
+10q	2.1	1.22066	[1, 3, 1, 2, 1, 4, 3, 4, 1, 1]
+1337	2.1	1.13578	[3, 1, 4, 0, 2, 3, 1, 2, 2, 3]
+143	3.2	0.74833	[4, 4, 2, 3, 2, 3, 4, 3, 4, 3]
+1432	2.6	0.8	[4, 3, 3, 2, 2, 4, 2, 2, 2, 2]
+14aa41	2.4	0.91652	[3, 2, 2, 4, 2, 2, 1, 2, 4, 2]
+182	-2.9	1.3	[-4, 0, -3, -3, -1, -3, -4, -4, -4, -3]
+187	-3.1	1.22066	[-4, 0, -4, -3, -2, -4, -3, -3, -4, -4]
+2g2b4g	2.8	0.6	[4, 2, 3, 2, 3, 3, 3, 3, 2, 3]
+2g2bt	-0.1	1.57797	[-1, 2, -1, 1, 0, 2, 0, -3, -2, 1]
+2qt	2.1	0.83066	[3, 3, 3, 3, 2, 1, 2, 1, 2, 1]
+3:(	-2.2	0.87178	[-4, -3, -2, -3, -2, -1, -1, -2, -2, -2]
+3:)	0.5	1.28452	[-2, 1, -2, 1, 1, 1, 1, 2, 1, 1]
+3:-(	-2.3	0.78102	[-2, -3, -2, -2, -2, -2, -4, -1, -3, -2]
+3:-)	-1.4	1.35647	[-1, -2, 1, 1, -2, -2, -3, -1, -3, -2]
+4col	-2.2	1.16619	[-2, -3, -1, -3, -4, -1, -2, -1, -4, -1]
+4q	-3.1	1.51327	[-3, -3, -4, -2, -4, -4, -4, 1, -4, -4]
+5fs	1.5	1.11803	[1, 2, 1, 1, 2, 3, 2, 3, -1, 1]
+8)	1.9	0.7	[2, 2, 2, 1, 1, 2, 2, 3, 3, 1]
+8-d	1.7	0.64031	[1, 2, 0, 2, 2, 2, 2, 2, 2, 2]
+8-o	-0.3	0.78102	[1, -1, 0, 0, 0, -1, 0, -2, 0, 0]
+86	-1.6	1.0198	[-1, -1, -1, -1, -1, -4, -1, -2, -1, -3]
+8d	2.9	0.53852	[3, 3, 4, 2, 3, 3, 3, 3, 2, 3]
+:###..	-2.4	0.91652	[-3, -2, -4, -3, -1, -2, -2, -3, -1, -3]
+:$	-0.2	1.83303	[-2, -1, 0, 0, -1, 1, 4, -3, 1, -1]
+:&	-0.6	1.0198	[-2, -1, 0, 0, -1, -1, 1, -2, 1, -1]
+:'(	-2.2	0.74833	[-2, -1, -2, -2, -2, -2, -4, -3, -2, -2]
+:')	2.3	0.78102	[3, 1, 3, 2, 2, 2, 2, 4, 2, 2]
+:'-(	-2.4	0.66332	[-2, -1, -2, -3, -2, -3, -3, -3, -2, -3]
+:'-)	2.7	0.64031	[2, 1, 3, 3, 3, 3, 3, 3, 3, 3]
+:(	-1.9	1.13578	[-2, -3, -2, 0, -1, -1, -2, -3, -1, -4]
+:)	2.0	1.18322	[2, 2, 1, 1, 1, 1, 4, 3, 4, 1]
+:*	2.5	1.0247	[3, 2, 1, 1, 2, 3, 4, 3, 4, 2]
+:-###..	-2.5	0.92195	[-3, -2, -3, -2, -4, -3, -1, -3, -1, -3]
+:-&	-0.5	0.92195	[-1, -1, 0, -1, -1, -1, -1, 0, 2, -1]
+:-(	-1.5	0.5	[-2, -1, -1, -1, -2, -2, -2, -1, -2, -1]
+:-)	1.3	0.45826	[1, 1, 1, 1, 2, 1, 2, 1, 2, 1]
+:-))	2.8	1.07703	[3, 4, 4, 1, 2, 2, 4, 2, 4, 2]
+:-*	1.7	0.64031	[1, 2, 1, 1, 1, 3, 2, 2, 2, 2]
+:-,	1.1	0.53852	[1, 1, 1, 0, 1, 1, 1, 1, 2, 2]
+:-.	-0.9	0.53852	[-1, -1, 0, -1, 0, -1, -1, -1, -2, -1]
+:-/	-1.2	0.6	[0, -1, -1, -1, -1, -2, -2, -1, -1, -2]
+:-<	-1.5	0.5	[-2, -1, -1, -2, -1, -2, -2, -1, -2, -1]
+:-d	2.3	0.45826	[2, 2, 3, 3, 2, 3, 2, 2, 2, 2]
+:-D	2.3	0.45826	[2, 2, 3, 3, 2, 3, 2, 2, 2, 2]
+:-o	0.1	1.3	[2, -1, -2, 0, 1, 1, 2, 0, -1, -1]
+:-p	1.2	0.4	[1, 2, 1, 1, 1, 1, 2, 1, 1, 1]
+:-[	-1.6	0.4899	[-1, -2, -1, -2, -2, -1, -2, -1, -2, -2]
+:-\	-0.9	0.3	[-1, -1, -1, -1, -1, -1, -1, 0, -1, -1]
+:-c	-1.3	0.45826	[-1, -1, -1, -2, -2, -1, -2, -1, -1, -1]
+:-p	1.5	0.5	[1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
+:-|	-0.7	0.64031	[-1, -1, 0, 0, 0, -1, -1, -2, 0, -1]
+:-||	-2.5	0.67082	[-2, -2, -2, -3, -2, -3, -3, -2, -2, -4]
+:-�	0.9	1.04403	[1, -1, 1, 2, 1, -1, 1, 2, 2, 1]
+:/	-1.4	0.66332	[-1, -1, -1, -1, -1, -1, -3, -2, -2, -1]
+:3	2.3	1.26886	[4, 1, 1, 1, 2, 2, 4, 3, 4, 1]
+:<	-2.1	0.7	[-3, -1, -2, -2, -2, -2, -3, -3, -2, -1]
+:>	2.1	1.22066	[3, 1, 1, 1, 1, 2, 4, 3, 4, 1]
+:?)	1.3	0.64031	[3, 1, 1, 1, 1, 2, 1, 1, 1, 1]
+:?c	-1.6	0.4899	[-1, -2, -1, -1, -2, -2, -1, -2, -2, -2]
+:@	-2.5	0.80623	[-1, -3, -3, -2, -1, -3, -3, -3, -3, -3]
+:d	2.3	1.1	[4, 2, 2, 1, 2, 1, 4, 3, 3, 1]
+:D	2.3	1.1	[4, 2, 2, 1, 2, 1, 4, 3, 3, 1]
+:l	-1.7	0.9	[-1, -3, -1, -1, -1, -3, -2, -3, -1, -1]
+:o	-0.4	1.35647	[2, -1, -2, 0, 1, 0, -3, 0, -1, 0]
+:p	1.0	0.7746	[-1, 1, 1, 1, 1, 1, 2, 1, 2, 1]
+:s	-1.2	0.9798	[-2, -2, -1, -1, -1, 1, -3, -1, -1, -1]
+:[	-2.0	0.63246	[-2, -2, -1, -2, -2, -3, -3, -2, -1, -2]
+:\	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -1, -1, -2]
+:]	2.2	1.16619	[3, 1, 1, 1, 3, 1, 4, 2, 2, 4]
+:^)	2.1	1.13578	[3, 2, 4, 1, 1, 1, 1, 2, 4, 2]
+:^*	2.6	0.91652	[2, 1, 2, 3, 4, 4, 3, 2, 3, 2]
+:^/	-1.2	0.6	[-2, -1, -2, 0, -1, -1, -1, -1, -2, -1]
+:^\	-1.0	0.44721	[-1, -1, -1, -1, -1, -2, 0, -1, -1, -1]
+:^|	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
+:c	-2.1	0.83066	[-3, -2, -1, -2, -2, -1, -3, -3, -3, -1]
+:c)	2.0	1.18322	[2, 1, 1, 1, 1, 2, 3, 4, 4, 1]
+:o)	2.1	0.9434	[1, 3, 3, 1, 1, 3, 2, 3, 1, 3]
+:o/	-1.4	0.4899	[-1, -1, -1, -2, -1, -1, -2, -2, -1, -2]
+:o\	-1.1	0.3	[-1, -1, -1, -2, -1, -1, -1, -1, -1, -1]
+:o|	-0.6	1.0198	[0, 0, 0, 0, -1, 0, 0, -3, 0, -2]
+:p	1.4	0.8	[3, 1, 0, 2, 1, 1, 2, 2, 1, 1]
+:{	-1.9	0.83066	[-2, -1, -1, -2, -2, -1, -3, -3, -3, -1]
+:|	-0.4	1.11355	[-1, -1, 0, -1, -1, -1, 1, -2, 2, 0]
+:}	2.1	1.22066	[3, 1, 1, 1, 2, 1, 4, 3, 4, 1]
+:�	1.1	0.53852	[1, 1, 1, 1, 0, 1, 1, 2, 2, 1]
+;)	0.9	1.04403	[2, -1, 1, 1, 1, 1, -1, 2, 2, 1]
+;-)	1.0	1.73205	[1, -2, 1, -2, 1, 4, 2, 1, 2, 2]
+;-*	2.2	0.74833	[2, 2, 1, 3, 4, 2, 2, 2, 2, 2]
+;-]	0.7	1.67631	[1, -2, 1, -3, 1, 2, 2, 1, 2, 2]
+;d	0.8	1.249	[2, -1, 2, 1, 1, 1, -2, 2, 1, 1]
+;D	0.8	1.249	[2, -1, 2, 1, 1, 1, -2, 2, 1, 1]
+;]	0.6	1.11355	[1, -1, 1, 1, 1, 1, -2, 2, 1, 1]
+;^)	1.4	0.91652	[2, 2, 1, 2, 1, 2, -1, 1, 2, 2]
+</3	-3.0	1.0	[-3, -3, -4, -3, -4, -1, -2, -2, -4, -4]
+<3	1.9	1.13578	[3, 2, 1, 3, 1, 4, 2, 0, 1, 2]
+<:	2.1	1.13578	[3, 2, 4, 1, 1, 1, 1, 2, 4, 2]
+<:-|	-1.4	0.66332	[-1, -1, -1, -2, -2, -1, -3, -1, -1, -1]
+=)	2.2	1.16619	[4, 2, 3, 3, 2, 1, 1, 4, 1, 1]
+=-3	2.0	0.63246	[2, 2, 2, 3, 1, 3, 1, 2, 2, 2]
+=-d	2.4	0.91652	[2, 2, 1, 3, 2, 4, 2, 4, 2, 2]
+=-D	2.4	0.91652	[2, 2, 1, 3, 2, 4, 2, 4, 2, 2]
+=/	-1.4	0.91652	[-1, -1, -1, -1, -1, -2, -1, -1, -4, -1]
+=3	2.1	0.7	[3, 1, 2, 1, 2, 3, 2, 2, 3, 2]
+=d	2.3	0.45826	[3, 2, 2, 2, 2, 3, 2, 2, 2, 3]
+=D	2.3	0.45826	[3, 2, 2, 2, 2, 3, 2, 2, 2, 3]
+=l	-1.2	0.6	[-2, -1, -1, 0, -2, -1, -2, -1, -1, -1]
+=\	-1.2	0.6	[-2, -1, -1, 0, -2, -1, -2, -1, -1, -1]
+=]	1.6	0.8	[2, 1, 3, 1, 1, 1, 2, 3, 1, 1]
+=p	1.3	0.9	[2, 1, 2, 1, 2, -1, 1, 2, 2, 1]
+=|	-0.8	0.87178	[-2, -1, -2, 1, 0, -1, 0, -1, -1, -1]
+>-:	-2.0	0.89443	[-2, -3, -2, -4, -1, -1, -1, -2, -2, -2]
+>.<	-1.3	0.45826	[-1, -2, -1, -2, -2, -1, -1, -1, -1, -1]
+>:	-2.1	1.13578	[-4, -1, -1, -4, -2, -3, -1, -1, -2, -2]
+>:(	-2.7	0.64031	[-2, -3, -2, -3, -3, -2, -4, -2, -3, -3]
+>:)	0.4	1.42829	[1, 1, 2, 1, -1, -2, 1, 2, -2, 1]
+>:-(	-2.7	0.78102	[-3, -2, -3, -2, -4, -2, -3, -2, -2, -4]
+>:-)	-0.4	1.68523	[1, 2, 1, -2, -2, -1, -1, -3, -1, 2]
+>:/	-1.6	0.8	[-1, -2, -1, -3, -1, -1, -1, -1, -2, -3]
+>:o	-1.2	1.16619	[-3, -1, -2, 0, -2, -2, 0, -1, 1, -2]
+>:p	1.0	0.7746	[-1, 1, 1, 2, 1, 2, 1, 1, 1, 1]
+>:[	-2.1	0.53852	[-2, -2, -2, -2, -3, -3, -2, -1, -2, -2]
+>:\	-1.7	0.64031	[-1, -2, -1, -2, -2, -3, -1, -1, -2, -2]
+>;(	-2.9	0.7	[-3, -4, -3, -2, -2, -3, -3, -3, -2, -4]
+>;)	0.1	1.04403	[-1, 1, 0, -1, 2, 0, -1, 1, 1, -1]
+>_>^	2.1	0.9434	[2, 2, 1, 4, 3, 2, 1, 3, 1, 2]
+@:	-2.1	0.9434	[-3, -2, -3, -1, -2, -4, -1, -2, -1, -2]
+@>-->--	2.1	1.22066	[1, 1, 0, 2, 4, 2, 4, 2, 3, 2]
+@}-;-'---	2.2	1.32665	[0, 1, 3, 2, 1, 4, 4, 1, 3, 3]
+aas	2.5	0.80623	[2, 3, 3, 4, 1, 2, 3, 2, 2, 3]
+aayf	2.7	0.78102	[2, 3, 2, 4, 3, 2, 2, 3, 4, 2]
+afu	-2.9	0.83066	[-3, -3, -3, -3, -3, -1, -4, -4, -2, -3]
+alol	2.8	0.74833	[2, 2, 2, 3, 3, 2, 3, 4, 4, 3]
+ambw	2.9	0.7	[2, 3, 4, 2, 3, 2, 3, 3, 4, 3]
+aml	3.4	0.66332	[4, 3, 2, 4, 3, 3, 4, 4, 3, 4]
+atab	-1.9	1.22066	[-2, 0, -1, -2, -1, -1, -2, -4, -4, -2]
+awol	-1.3	0.78102	[0, -1, -1, -1, -1, -1, -2, -2, -3, -1]
+ayc	0.2	0.9798	[0, 1, -1, 1, 0, 1, 0, -1, 2, -1]
+ayor	-1.2	0.6	[-1, -1, -2, -2, -1, -1, -1, 0, -2, -1]
+aug-00	0.3	1.18743	[2, 0, -2, 0, 0, 1, -1, 2, 1, 0]
+bfd	-2.7	0.78102	[-3, -2, -4, -2, -3, -2, -3, -2, -4, -2]
+bfe	-2.6	1.35647	[-3, -3, -4, -2, -3, -2, 1, -3, -4, -3]
+bff	2.9	0.83066	[3, 3, 4, 2, 4, 2, 2, 3, 4, 2]
+bffn	1.0	0.89443	[2, 1, -1, 1, 0, 1, 2, 1, 2, 1]
+bl	2.3	1.1	[2, 1, 4, 1, 2, 2, 4, 3, 1, 3]
+bsod	-2.2	1.07703	[-1, -4, -3, -3, 0, -2, -3, -2, -2, -2]
+btd	-2.1	0.83066	[-1, -2, -3, -3, -3, -1, -3, -2, -1, -2]
+btdt	-0.1	1.22066	[0, -1, 0, -1, 0, 3, 1, -1, -1, -1]
+bz	0.4	1.35647	[-1, 0, 0, 0, 4, 1, -1, 1, 0, 0]
+b^d	2.6	0.8	[3, 2, 2, 4, 3, 1, 3, 3, 3, 2]
+cwot	-2.3	0.45826	[-3, -2, -2, -2, -2, -3, -2, -3, -2, -2]
+d-':	-2.5	0.67082	[-3, -3, -2, -2, -2, -4, -2, -3, -2, -2]
+d8	-3.2	0.6	[-3, -3, -3, -3, -4, -4, -2, -3, -3, -4]
+d:	-2.9	0.83066	[-3, -3, -3, -3, -2, -4, -1, -3, -3, -4]
+d:<	-3.2	0.9798	[-4, -4, -4, -1, -3, -3, -4, -2, -3, -4]
+d;	-2.9	0.83066	[-1, -3, -3, -3, -3, -4, -2, -3, -3, -4]
+d=	-3.0	0.89443	[-4, -3, -3, -3, -2, -4, -1, -3, -3, -4]
+doa	-2.3	1.00499	[-2, -3, -3, -2, -2, -2, -4, 0, -2, -3]
+dx	-3.0	0.63246	[-3, -2, -3, -3, -4, -3, -4, -2, -3, -3]
+ez	1.5	0.67082	[3, 2, 2, 1, 1, 1, 2, 1, 1, 1]
+fav	2.4	0.91652	[3, 1, 3, 2, 2, 3, 1, 2, 3, 4]
+fcol	-1.8	0.74833	[-2, -2, -1, -2, -1, -2, -1, -3, -3, -1]
+ff	1.8	1.249	[4, 2, 1, 2, 1, 3, 3, 0, 2, 0]
+ffs	-2.8	0.9798	[-2, -2, -3, -3, -2, -4, -4, -4, -1, -3]
+fkm	-2.4	1.35647	[-4, -1, -4, -2, -2, -3, -1, 0, -3, -4]
+foaf	1.8	1.249	[2, 1, 2, 0, 4, 1, 1, 1, 2, 4]
+ftw	2.0	0.7746	[2, 1, 1, 2, 2, 2, 3, 3, 1, 3]
+fu	-3.7	0.45826	[-3, -4, -4, -3, -3, -4, -4, -4, -4, -4]
+fubar	-3.0	1.09545	[-4, -3, -3, -4, -3, -3, -3, -4, 0, -3]
+fwb	2.5	1.43178	[2, 3, 4, 0, 1, 2, 4, 1, 4, 4]
+fyi	0.8	1.66132	[0, 1, 0, -1, 0, 0, 4, 4, 0, 0]
+fysa	0.4	0.91652	[0, 0, 0, 1, 0, 3, 0, 0, 0, 0]
+g1	1.4	0.4899	[2, 1, 1, 1, 2, 1, 2, 1, 1, 2]
+gg	1.2	0.74833	[0, 2, 2, 1, 0, 1, 2, 2, 1, 1]
+gga	1.7	0.45826	[2, 2, 1, 2, 2, 1, 2, 2, 1, 2]
+gigo	-0.6	1.11355	[-2, -1, 1, 0, 0, 0, -1, -2, -2, 1]
+gj	2.0	1.0	[2, 1, 2, 1, 1, 3, 4, 2, 3, 1]
+gl	1.3	0.64031	[1, 1, 1, 1, 3, 1, 1, 2, 1, 1]
+gla	2.5	0.92195	[1, 2, 2, 4, 2, 4, 2, 3, 3, 2]
+gn	1.2	0.74833	[1, 1, 1, 1, 3, 1, 1, 2, 1, 0]
+gr8	2.7	0.78102	[1, 3, 3, 4, 3, 2, 3, 2, 3, 3]
+grrr	-0.4	1.42829	[-2, -1, 0, 1, -2, -1, -1, 3, 0, -1]
+gt	1.1	0.53852	[1, 1, 1, 1, 1, 1, 2, 1, 0, 2]
+h&k	2.3	0.78102	[2, 2, 2, 3, 4, 2, 3, 2, 1, 2]
+hagd	2.2	0.87178	[2, 2, 3, 2, 1, 3, 4, 1, 2, 2]
+hagn	2.2	0.87178	[2, 2, 3, 2, 1, 3, 4, 1, 2, 2]
+hago	1.2	0.4	[1, 2, 1, 1, 1, 2, 1, 1, 1, 1]
+hak	1.9	0.7	[3, 1, 2, 2, 1, 2, 3, 2, 1, 2]
+hand	2.2	0.87178	[2, 2, 1, 3, 2, 3, 4, 1, 2, 2]
+hho1/2k	1.4	1.11355	[1, -1, 2, 3, 1, 1, 1, 2, 3, 1]
+hhoj	2.0	1.09545	[4, 2, 1, 1, 2, 1, 1, 4, 2, 2]
+hhok	0.9	0.9434	[1, 2, 1, 0, -1, 0, 2, 1, 1, 2]
+hugz	2.0	0.7746	[2, 3, 1, 3, 1, 3, 1, 2, 2, 2]
+hi5	1.9	0.53852	[2, 2, 2, 1, 3, 2, 1, 2, 2, 2]
+idk	-0.4	0.66332	[0, 0, 0, 0, -1, -2, 0, 0, 0, -1]
+ijs	0.7	1.84662	[0, -1, 0, -1, 0, 4, 0, 4, -1, 2]
+ilu	3.4	0.66332	[3, 4, 3, 4, 2, 3, 4, 3, 4, 4]
+iluaaf	2.7	1.1	[3, 3, 3, 2, 3, 0, 4, 3, 2, 4]
+ily	3.4	0.66332	[3, 4, 3, 4, 2, 3, 4, 3, 4, 4]
+ily2	2.6	0.66332	[3, 2, 3, 2, 3, 2, 3, 4, 2, 2]
+iou	0.7	1.34536	[0, 0, -1, 2, 0, 0, 0, 4, 1, 1]
+iyq	2.3	1.18743	[3, 3, 1, 1, 2, 1, 4, 4, 3, 1]
+j/j	2.0	1.34164	[4, 1, 1, 1, 1, 4, 4, 1, 2, 1]
+j/k	1.6	1.2	[1, 2, 1, 3, 0, 0, 2, 2, 1, 4]
+j/p	1.4	0.66332	[1, 1, 0, 2, 1, 2, 2, 2, 1, 2]
+j/t	-0.2	1.46969	[1, -1, -1, -2, 1, 1, 2, -2, 1, -2]
+j/w	1.0	1.0	[1, 1, 1, 3, 0, 0, 0, 2, 0, 2]
+j4f	1.4	0.8	[2, 1, 1, 0, 3, 1, 1, 1, 2, 2]
+j4g	1.7	1.18743	[1, 4, 1, 1, 3, 1, 3, 0, 2, 1]
+jho	0.8	0.4	[1, 1, 1, 1, 0, 1, 1, 1, 0, 1]
+jhomf	1.0	0.63246	[1, 1, 1, 0, 1, 0, 2, 2, 1, 1]
+jj	1.0	0.63246	[1, 1, 1, 1, 2, 0, 2, 1, 1, 0]
+jk	0.9	1.22066	[1, 0, 0, 1, 0, 0, 2, 1, 4, 0]
+jp	0.8	0.74833	[1, 1, 1, 0, 2, 0, 2, 0, 1, 0]
+jt	0.9	0.83066	[1, 1, 0, 2, 2, 0, 2, 0, 1, 0]
+jw	1.6	1.68523	[3, 0, 0, 0, 0, 0, 3, 4, 2, 4]
+jealz	-1.2	0.9798	[-1, -1, -1, 1, -2, -2, -1, -3, -1, -1]
+k4y	2.3	1.00499	[2, 1, 1, 2, 4, 2, 3, 4, 2, 2]
+kfy	2.3	0.64031	[2, 2, 2, 1, 3, 2, 3, 3, 2, 3]
+kia	-3.2	0.6	[-3, -3, -3, -4, -3, -2, -3, -3, -4, -4]
+kk	1.5	1.0247	[2, 1, 0, 0, 1, 2, 3, 3, 2, 1]
+kmuf	2.2	1.4	[2, 2, 2, 3, 4, 3, -1, 1, 4, 2]
+l	2.0	0.7746	[2, 1, 2, 3, 2, 3, 1, 3, 2, 1]
+l&r	2.2	0.74833	[3, 2, 2, 3, 1, 3, 1, 3, 2, 2]
+laoj	1.3	1.73494	[1, -2, -1, 3, 3, 2, 4, 1, 1, 1]
+lmao	2.0	1.18322	[3, 0, 3, 0, 3, 1, 3, 2, 3, 2]
+lmbao	1.8	1.77764	[3, 2, 2, 2, 1, 3, -3, 2, 4, 2]
+lmfao	2.5	1.28452	[3, 2, 3, 3, 3, -1, 4, 2, 3, 2]
+lmso	2.7	0.78102	[3, 3, 4, 3, 3, 1, 3, 3, 2, 2]
+lol	2.9	0.83066	[4, 2, 2, 2, 4, 2, 3, 3, 4, 3]
+lolz	2.7	0.78102	[2, 3, 3, 2, 2, 4, 4, 3, 2, 2]
+lts	1.6	0.66332	[1, 1, 2, 2, 1, 3, 1, 1, 2, 2]
+ly	2.6	0.91652	[2, 2, 1, 3, 4, 4, 3, 2, 2, 3]
+ly4e	2.7	0.78102	[3, 3, 3, 2, 1, 3, 3, 4, 2, 3]
+lya	3.3	0.78102	[3, 4, 4, 4, 2, 2, 3, 4, 3, 4]
+lyb	3.0	0.63246	[3, 3, 4, 3, 2, 3, 2, 4, 3, 3]
+lyl	3.1	0.7	[4, 3, 4, 3, 2, 3, 3, 2, 4, 3]
+lylab	2.7	0.78102	[3, 3, 3, 1, 3, 4, 2, 2, 3, 3]
+lylas	2.6	0.8	[3, 3, 3, 1, 3, 4, 2, 2, 2, 3]
+lylb	1.6	1.56205	[2, 2, 3, -2, 4, 1, 3, 1, 1, 1]
+m8	1.4	1.0198	[3, 0, 1, 0, 1, 3, 2, 2, 1, 1]
+mia	-1.2	0.4	[-2, -1, -1, -2, -1, -1, -1, -1, -1, -1]
+mml	2.0	1.0	[1, 1, 2, 3, 3, 2, 1, 2, 4, 1]
+mofo	-2.4	2.2	[-4, -4, -4, 0, -3, -2, -2, -4, 3, -4]
+muah	2.8	1.07703	[1, 2, 4, 4, 4, 2, 4, 2, 2, 3]
+mubar	-1.0	2.36643	[-4, -2, -3, -2, -2, -2, 1, 4, 2, -2]
+musm	0.9	2.07123	[-1, 1, 1, 1, 4, 3, 1, -4, 1, 2]
+mwah	2.5	0.80623	[2, 2, 2, 4, 2, 3, 2, 2, 4, 2]
+n1	1.9	1.04403	[1, 1, 3, 2, 2, 3, 4, 1, 1, 1]
+nbd	1.3	1.34536	[2, 1, 0, 0, 0, 4, 2, 0, 3, 1]
+nbif	-0.5	0.67082	[-1, -2, 0, 0, 0, 0, -1, -1, 0, 0]
+nfc	-2.7	0.9	[-3, -2, -2, -3, -1, -2, -4, -3, -4, -3]
+nfw	-2.4	1.0198	[-2, -2, -1, -3, -1, -2, -4, -3, -4, -2]
+nh	2.2	0.6	[2, 2, 2, 2, 1, 3, 3, 3, 2, 2]
+nimby	-0.8	0.6	[0, 0, -1, 0, -1, -2, -1, -1, -1, -1]
+nimjd	-0.7	0.78102	[0, -2, -1, -2, 0, -1, 0, 0, 0, -1]
+nimq	-0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, -2, 0]
+nimy	-1.4	1.68523	[-1, -2, -3, -2, -1, 2, -3, 0, 0, -4]
+nitl	-1.5	0.92195	[-1, -1, -2, -3, -1, -3, -1, -2, 0, -1]
+nme	-2.1	1.13578	[-1, -2, -2, -1, -4, -2, -3, -3, 0, -3]
+noyb	-0.7	1.67631	[-1, -2, 0, -1, -1, -2, -2, -1, 4, -1]
+np	1.4	1.0198	[0, 1, 1, 1, 1, 2, 2, 4, 1, 1]
+ntmu	1.4	0.66332	[1, 1, 0, 1, 2, 2, 2, 2, 2, 1]
+o-8	-0.5	1.5	[2, -1, 0, 0, -2, -2, 0, -2, 2, -2]
+o-:	-0.3	1.18743	[2, -1, 0, 0, -1, -2, 0, -2, 1, 0]
+o-|	-1.1	0.53852	[-1, -1, -1, 0, -1, -1, -1, -2, -2, -1]
+o.o	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
+O.o	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
+o.O	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
+o:	-0.2	0.87178	[-1, 0, -1, -2, 0, 1, 0, 1, 0, 0]
+o:)	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
+o:-)	2.0	1.18322	[1, 4, 1, 2, 4, 1, 1, 2, 3, 1]
+o:-3	2.2	0.9798	[1, 4, 2, 3, 3, 2, 1, 2, 3, 1]
+o:3	2.3	0.78102	[3, 3, 2, 2, 1, 2, 4, 2, 2, 2]
+o:<	-0.3	1.1	[-1, -1, -2, 0, -1, 0, 1, 2, 0, -1]
+o;^)	1.6	0.8	[1, 2, 1, 2, 1, 2, 2, 0, 3, 2]
+ok	1.6	1.42829	[0, 0, 1, 1, 1, 4, 3, 4, 1, 1]
+o_o	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
+O_o	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
+o_O	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
+pita	-2.4	1.2	[-2, -1, -1, -4, -4, -2, -4, -2, -3, -1]
+pls	0.3	0.45826	[0, 1, 1, 1, 0, 0, 0, 0, 0, 0]
+plz	0.3	0.45826	[0, 1, 1, 1, 0, 0, 0, 0, 0, 0]
+pmbi	0.8	1.32665	[3, 0, 0, 1, 1, -2, 2, 2, 0, 1]
+pmfji	0.3	0.78102	[0, 0, 1, 0, 2, -1, 0, 1, 0, 0]
+pmji	0.7	1.00499	[1, 2, 0, -1, 0, 0, 2, 2, 1, 0]
+po	-2.6	0.91652	[-2, -3, -4, -3, -3, -3, -1, -3, -1, -3]
+ptl	2.6	1.11355	[3, 4, 2, 4, 1, 2, 3, 1, 4, 2]
+pu	-1.1	1.3	[-3, -1, -3, -2, -1, -1, -1, -1, 1, 1]
+qq	-2.2	0.6	[-2, -2, -1, -3, -3, -2, -2, -3, -2, -2]
+qt	1.8	0.6	[2, 2, 1, 2, 1, 3, 2, 1, 2, 2]
+r&r	2.4	1.0198	[2, 4, 2, 3, 1, 4, 2, 2, 1, 3]
+rofl	2.7	0.78102	[3, 2, 2, 2, 4, 4, 2, 3, 3, 2]
+roflmao	2.5	1.11803	[4, 2, 2, 4, 1, 1, 2, 4, 3, 2]
+rotfl	2.6	0.66332	[3, 2, 3, 3, 1, 3, 3, 3, 2, 3]
+rotflmao	2.8	1.07703	[4, 3, 2, 4, 1, 1, 4, 3, 3, 3]
+rotflmfao	2.5	1.11803	[3, 4, 1, 3, 3, 3, 0, 3, 2, 3]
+rotflol	3.0	1.09545	[1, 4, 4, 4, 2, 2, 2, 3, 4, 4]
+rotgl	2.9	0.7	[4, 3, 2, 2, 3, 3, 3, 2, 4, 3]
+rotglmao	1.8	2.4	[3, 3, 4, 3, -1, 1, 4, -4, 2, 3]
+s:	-1.1	0.83066	[-1, -1, -2, -2, -1, -1, -2, -1, 1, -1]
+sapfu	-1.1	1.57797	[-2, 0, -3, -1, -1, 1, -2, 2, -2, -3]
+sete	2.8	0.87178	[3, 3, 3, 2, 3, 3, 4, 4, 1, 2]
+sfete	2.7	0.78102	[4, 3, 3, 3, 2, 4, 2, 2, 2, 2]
+sgtm	2.4	1.0198	[2, 1, 1, 2, 3, 3, 2, 2, 4, 4]
+slap	0.6	2.15407	[2, -1, 1, -1, 0, 4, -3, 4, 1, -1]
+slaw	2.1	1.04403	[3, 2, 0, 2, 2, 2, 3, 1, 4, 2]
+smh	-1.3	0.64031	[-2, -1, 0, -1, -1, -2, -2, -1, -2, -1]
+snafu	-2.5	1.11803	[-3, -4, -3, -3, -1, 0, -2, -3, -3, -3]
+sob	-2.8	0.9798	[-3, -4, -3, -2, -2, -1, -2, -4, -4, -3]
+swak	2.3	1.00499	[2, 2, 2, 1, 4, 2, 3, 2, 1, 4]
+tgif	2.3	1.34536	[1, 3, 3, 3, -1, 2, 4, 2, 3, 3]
+thks	1.4	0.4899	[1, 2, 1, 2, 1, 2, 1, 1, 2, 1]
+thx	1.5	0.92195	[0, 1, 3, 2, 1, 2, 1, 1, 3, 1]
+tia	2.3	0.9	[3, 1, 2, 1, 4, 3, 2, 3, 2, 2]
+tmi	-0.3	1.61555	[-1, -1, 2, -1, 1, -2, -2, -1, 3, -1]
+tnx	1.1	0.53852	[2, 1, 1, 0, 1, 1, 2, 1, 1, 1]
+true	1.8	1.32665	[2, 1, 1, 0, 1, 4, 3, 1, 4, 1]
+tx	1.5	0.92195	[3, 2, 1, 0, 2, 1, 3, 1, 1, 1]
+txs	1.1	0.7	[1, 2, 0, 1, 2, 0, 1, 2, 1, 1]
+ty	1.6	0.66332	[1, 2, 3, 1, 2, 2, 1, 2, 1, 1]
+tyvm	2.5	1.11803	[2, 2, 1, 3, 1, 4, 2, 4, 2, 4]
+urw	1.9	1.13578	[1, 2, 1, 2, 4, 2, 4, 1, 1, 1]
+vbg	2.1	1.75784	[2, 3, 3, 3, 3, -3, 3, 2, 2, 3]
+vbs	3.1	0.53852	[2, 3, 3, 3, 4, 4, 3, 3, 3, 3]
+vip	2.3	1.00499	[2, 1, 1, 3, 4, 2, 2, 4, 2, 2]
+vwd	2.6	0.91652	[4, 2, 4, 2, 1, 3, 3, 2, 3, 2]
+vwp	2.1	0.7	[3, 1, 2, 2, 3, 2, 2, 3, 1, 2]
+wag	-0.2	0.74833	[-1, 0, 0, 0, 0, 0, -2, 1, 0, 0]
+wd	2.7	1.1	[3, 1, 4, 3, 4, 2, 1, 3, 2, 4]
+wilco	0.9	0.9434	[1, 3, 1, 0, 1, 0, 2, 1, 0, 0]
+wp	1.0	0.0	[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+wtf	-2.8	0.74833	[-4, -3, -2, -3, -2, -2, -2, -4, -3, -3]
+wtg	2.1	0.7	[1, 3, 2, 3, 2, 2, 2, 1, 2, 3]
+wth	-2.4	0.4899	[-2, -3, -2, -3, -2, -2, -2, -3, -3, -2]
+x-d	2.7	0.78102	[1, 3, 4, 2, 3, 3, 3, 2, 3, 3]
+x-p	1.8	0.87178	[2, 1, 3, 1, 3, 1, 3, 1, 2, 1]
+xd	2.7	0.9	[1, 4, 4, 3, 2, 2, 3, 3, 2, 3]
+xlnt	3.0	0.89443	[4, 3, 3, 1, 4, 4, 3, 3, 3, 2]
+xoxo	3.0	0.7746	[2, 2, 4, 2, 3, 3, 4, 3, 3, 4]
+xoxozzz	2.3	0.78102	[3, 1, 2, 2, 2, 2, 3, 2, 4, 2]
+xp	1.2	0.4	[1, 1, 1, 1, 2, 1, 2, 1, 1, 1]
+xqzt	1.6	1.42829	[0, 2, 1, 2, 4, -1, 3, 1, 1, 3]
+xtc	0.8	1.93907	[2, 0, -3, 3, 3, -1, 3, 1, -1, 1]
+yolo	1.1	0.83066	[0, 1, 1, 2, 1, 1, 1, 3, 0, 1]
+yoyo	0.4	1.85472	[-1, 0, -1, -1, 4, 2, -2, 2, 2, -1]
+yvw	1.6	0.4899	[1, 2, 1, 1, 2, 2, 2, 1, 2, 2]
+yw	1.8	1.32665	[1, 1, 1, 4, 1, 1, 4, 0, 3, 2]
+ywia	2.5	1.11803	[3, 2, 3, 4, 1, 1, 1, 3, 3, 4]
+zzz	-1.2	0.87178	[0, -1, 0, -1, -3, -1, -1, -2, -2, -1]
+[-;	0.5	1.28452	[1, -1, -1, 1, 1, 1, 2, -2, 2, 1]
+[:	1.3	0.45826	[1, 1, 2, 1, 2, 2, 1, 1, 1, 1]
+[;	1.0	1.34164	[2, 1, 2, 2, 1, 2, 2, -2, -1, 1]
+[=	1.7	0.64031	[2, 2, 1, 1, 1, 2, 2, 3, 2, 1]
+\-:	-1.0	1.18322	[-3, -1, -1, -1, -1, -1, 2, -2, -1, -1]
+\:	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
+\:<	-1.7	1.18743	[-1, -3, -2, -2, -3, -3, -2, -1, 1, -1]
+\=	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -1, -2, -1, -1]
+\^:	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -1, -2, -2, -1]
+\o/	2.2	0.9798	[2, 1, 1, 2, 4, 2, 2, 4, 2, 2]
+\o:	-1.2	0.4	[-1, -1, -1, -1, -2, -1, -1, -2, -1, -1]
+]-:	-2.1	0.53852	[-2, -3, -3, -2, -2, -2, -1, -2, -2, -2]
+]:	-1.6	0.66332	[-1, -2, -1, -2, -3, -2, -1, -1, -1, -2]
+]:<	-2.5	0.80623	[-2, -2, -2, -3, -4, -2, -2, -2, -2, -4]
+^<_<	1.4	1.11355	[3, 1, 3, 2, 1, 1, 1, -1, 2, 1]
+^urs	-2.8	0.6	[-2, -3, -3, -2, -3, -3, -2, -3, -4, -3]
+abandon	-1.9	0.53852	[-1, -2, -2, -2, -2, -3, -2, -2, -1, -2]
+abandoned	-2.0	1.09545	[-1, -1, -3, -2, -1, -4, -1, -3, -3, -1]
+abandoner	-1.9	0.83066	[-1, -1, -3, -2, -1, -3, -1, -2, -3, -2]
+abandoners	-1.9	0.83066	[-2, -3, -2, -3, -2, -1, -2, -2, 0, -2]
+abandoning	-1.6	0.8	[-3, -2, -3, -2, -1, -1, -1, -1, -1, -1]
+abandonment	-2.4	1.0198	[-4, -2, -1, -4, -2, -1, -2, -3, -3, -2]
+abandonments	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
+abandons	-1.3	0.9	[-2, -1, -1, -2, -1, -2, -1, -2, 1, -2]
+abducted	-2.3	1.18743	[-3, -1, 0, -3, -1, -3, -4, -2, -3, -3]
+abduction	-2.8	0.87178	[-4, -3, -3, -4, -1, -3, -2, -2, -3, -3]
+abductions	-2.0	1.41421	[-3, -4, -1, -3, -1, -3, 1, -2, -1, -3]
+abhor	-2.0	1.09545	[-3, -3, -1, -1, -2, -1, -3, -3, 0, -3]
+abhorred	-2.4	1.49666	[-4, -4, 0, -3, -2, -1, -4, -3, -3, 0]
+abhorrent	-3.1	1.3	[-4, -4, -4, -2, 0, -4, -2, -3, -4, -4]
+abhors	-2.9	1.51327	[0, -4, -3, -3, -4, -4, 0, -4, -3, -4]
+abilities	1.0	0.63246	[1, 2, 0, 1, 0, 1, 1, 1, 1, 2]
+ability	1.3	0.64031	[1, 1, 1, 0, 1, 2, 2, 2, 2, 1]
+aboard	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+absentee	-1.1	0.53852	[-1, -1, 0, -2, -1, -1, -2, -1, -1, -1]
+absentees	-0.8	0.6	[-1, 0, 0, -1, -1, 0, -2, -1, -1, -1]
+absolve	1.2	1.46969	[2, -3, 2, 2, 1, 1, 2, 1, 2, 2]
+absolved	1.5	0.92195	[3, 1, 2, 1, 0, 2, 3, 1, 1, 1]
+absolves	1.3	1.00499	[3, 1, 1, 0, 0, 2, 3, 1, 1, 1]
+absolving	1.6	0.8	[3, 1, 2, 1, 1, 2, 3, 1, 1, 1]
+abuse	-3.2	0.6	[-4, -2, -3, -4, -3, -4, -3, -3, -3, -3]
+abused	-2.3	0.64031	[-2, -2, -3, -2, -2, -4, -2, -2, -2, -2]
+abuser	-2.6	0.4899	[-3, -2, -3, -3, -2, -3, -2, -2, -3, -3]
+abusers	-2.6	1.0198	[-2, -3, -3, -3, -3, -2, -3, -4, -3, 0]
+abuses	-2.6	0.66332	[-3, -2, -3, -3, -3, -3, -1, -2, -3, -3]
+abusing	-2.0	1.41421	[-1, -2, -2, -4, -4, -2, -3, -1, 1, -2]
+abusive	-3.2	0.74833	[-4, -3, -3, -4, -4, -3, -4, -2, -3, -2]
+abusively	-2.8	0.6	[-3, -4, -3, -2, -3, -2, -2, -3, -3, -3]
+abusiveness	-2.5	0.92195	[-2, -4, -2, -3, -2, -3, -4, -2, -1, -2]
+abusivenesses	-3.0	0.63246	[-3, -3, -4, -3, -4, -2, -2, -3, -3, -3]
+accept	1.6	0.91652	[2, 1, 2, 1, 1, 2, 4, 1, 1, 1]
+acceptabilities	1.6	0.66332	[0, 2, 2, 2, 1, 2, 2, 2, 1, 2]
+acceptability	1.1	0.53852	[1, 0, 1, 2, 1, 2, 1, 1, 1, 1]
+acceptable	1.3	0.45826	[1, 2, 1, 1, 1, 2, 1, 1, 2, 1]
+acceptableness	1.3	0.9	[1, 0, 2, 1, 2, 1, 1, 0, 2, 3]
+acceptably	1.5	0.67082	[3, 2, 1, 1, 1, 2, 1, 1, 2, 1]
+acceptance	2.0	0.63246	[3, 1, 3, 2, 1, 2, 2, 2, 2, 2]
+acceptances	1.7	0.78102	[3, 1, 1, 1, 2, 2, 1, 2, 3, 1]
+acceptant	1.6	0.8	[0, 1, 2, 2, 2, 1, 2, 1, 3, 2]
+acceptation	1.3	0.78102	[0, 1, 2, 1, 1, 1, 1, 3, 2, 1]
+acceptations	0.9	0.83066	[1, 2, 0, 2, 0, 1, 0, 2, 1, 0]
+accepted	1.1	0.3	[1, 1, 1, 1, 1, 2, 1, 1, 1, 1]
+accepting	1.6	0.66332	[2, 2, 2, 1, 1, 2, 1, 3, 1, 1]
+accepts	1.3	0.45826	[1, 2, 1, 1, 1, 2, 2, 1, 1, 1]
+accident	-2.1	0.83066	[-2, -2, -1, -3, -4, -2, -2, -1, -2, -2]
+accidental	-0.3	0.45826	[-1, -1, 0, 0, 0, 0, 0, 0, -1, 0]
+accidentally	-1.4	0.91652	[-2, 0, -2, 0, -3, -1, -1, -1, -2, -2]
+accidents	-1.3	0.78102	[-1, -1, -1, -1, -2, 0, -3, -1, -2, -1]
+accomplish	1.8	0.6	[1, 2, 3, 2, 2, 2, 1, 1, 2, 2]
+accomplished	1.9	0.53852	[2, 2, 2, 1, 2, 2, 3, 1, 2, 2]
+accomplishes	1.7	0.9	[2, 2, 1, 0, 2, 3, 3, 1, 1, 2]
+accusation	-1.0	1.09545	[-1, -1, -2, -2, -2, -1, -1, -1, 2, -1]
+accusations	-1.3	1.26886	[-2, -2, -1, -3, -2, -1, -1, 2, -2, -1]
+accuse	-0.8	1.53623	[-3, -1, -1, -2, 1, -2, 1, -2, 2, -1]
+accused	-1.2	1.46969	[-2, -1, -2, 2, -2, -3, -2, -2, -1, 1]
+accuses	-1.4	1.0198	[-2, -1, -2, 1, -2, -3, -1, -2, -1, -1]
+accusing	-0.7	1.34536	[-2, -1, -1, 1, -3, -1, -1, 2, -1, 0]
+ache	-1.6	1.2	[-1, -2, -2, -2, -1, -4, -1, 1, -2, -2]
+ached	-1.6	0.8	[-2, -2, -1, -2, -1, -2, -3, 0, -1, -2]
+aches	-1.0	0.7746	[-1, -2, -1, -1, -1, 1, -2, -1, -1, -1]
+achievable	1.3	0.45826	[2, 1, 1, 1, 1, 1, 1, 2, 2, 1]
+aching	-2.2	0.74833	[-2, -3, -2, -1, -3, -3, -2, -3, -1, -2]
+acquit	0.8	1.72047	[-3, 3, -1, 3, 2, 1, 1, 1, 0, 1]
+acquits	0.1	1.37477	[1, -3, -1, 0, 2, 0, -1, 1, 1, 1]
+acquitted	1.0	0.89443	[2, 2, 1, 1, 2, 0, 1, 1, -1, 1]
+acquitting	1.3	0.78102	[3, 2, 0, 1, 1, 1, 2, 1, 1, 1]
+acrimonious	-1.7	1.73494	[-1, -3, -2, -3, 3, -3, -1, -2, -2, -3]
+active	1.7	1.26886	[1, 2, 1, 1, 1, 4, 2, 4, 0, 1]
+actively	1.3	0.78102	[0, 1, 0, 2, 2, 1, 1, 2, 2, 2]
+activeness	0.6	0.8	[0, 2, 0, 0, 1, 0, 1, 0, 2, 0]
+activenesses	0.8	0.74833	[2, 0, 1, 0, 0, 0, 1, 2, 1, 1]
+actives	1.1	0.7	[2, 1, 0, 1, 1, 0, 1, 1, 2, 2]
+adequate	0.9	0.7	[0, 0, 1, 1, 0, 2, 1, 1, 2, 1]
+admirability	2.4	0.4899	[2, 3, 3, 3, 3, 2, 2, 2, 2, 2]
+admirable	2.6	0.66332	[2, 3, 3, 3, 4, 3, 2, 2, 2, 2]
+admirableness	2.2	0.87178	[2, 2, 3, 3, 3, 1, 3, 1, 3, 1]
+admirably	2.5	0.67082	[2, 3, 3, 3, 4, 2, 2, 2, 2, 2]
+admiral	1.3	1.18743	[0, 0, 1, 3, 3, 2, 2, 0, 2, 0]
+admirals	1.5	0.80623	[2, 2, 0, 2, 2, 0, 1, 2, 2, 2]
+admiralties	1.6	0.66332	[2, 2, 2, 1, 0, 2, 2, 2, 1, 2]
+admiralty	1.2	1.53623	[0, 4, 0, 0, 0, 2, 2, 3, 2, -1]
+admiration	2.5	0.80623	[3, 1, 1, 3, 3, 2, 3, 3, 3, 3]
+admirations	1.6	0.66332	[2, 2, 1, 1, 2, 2, 2, 2, 2, 0]
+admire	2.1	0.83066	[3, 3, 1, 3, 3, 2, 1, 2, 1, 2]
+admired	2.3	0.78102	[4, 2, 2, 2, 2, 2, 3, 3, 1, 2]
+admirer	1.8	0.74833	[2, 1, 1, 2, 3, 2, 3, 1, 1, 2]
+admirers	1.7	1.00499	[2, 3, 2, 2, 2, 1, -1, 2, 2, 2]
+admires	1.5	0.67082	[3, 1, 1, 2, 1, 2, 2, 1, 1, 1]
+admiring	1.6	0.8	[1, 2, 1, 1, 3, 3, 2, 1, 1, 1]
+admiringly	2.3	0.64031	[1, 3, 3, 2, 2, 2, 2, 3, 3, 2]
+admit	0.8	1.07703	[0, 0, 0, 0, 0, 1, 3, 2, 2, 0]
+admits	1.2	0.87178	[1, 2, 2, 2, 0, 0, 1, 2, 0, 2]
+admitted	0.4	0.66332	[0, 1, 0, 1, 0, 0, 2, 0, 0, 0]
+admonished	-1.9	0.9434	[-2, -2, -2, -1, -2, -3, -1, -1, -1, -4]
+adopt	0.7	0.64031	[0, 0, 1, 1, 1, 0, 1, 0, 1, 2]
+adopts	0.7	0.64031	[0, 0, 1, 2, 1, 0, 1, 1, 0, 1]
+adorability	2.2	0.74833	[2, 2, 2, 2, 1, 2, 3, 2, 4, 2]
+adorable	2.2	0.6	[3, 2, 2, 3, 2, 2, 1, 3, 2, 2]
+adorableness	2.5	0.67082	[2, 3, 3, 2, 3, 2, 1, 3, 3, 3]
+adorably	2.1	0.7	[3, 1, 2, 3, 2, 2, 1, 3, 2, 2]
+adoration	2.9	0.7	[3, 3, 3, 2, 3, 3, 4, 2, 4, 2]
+adorations	2.2	0.87178	[2, 2, 3, 1, 3, 1, 3, 3, 1, 3]
+adore	2.6	0.91652	[3, 3, 1, 2, 3, 3, 3, 4, 1, 3]
+adored	1.8	0.87178	[2, 3, 3, 2, 2, 1, 1, 0, 2, 2]
+adorer	1.7	1.1	[2, 4, 3, 1, 2, 1, 1, 0, 2, 1]
+adorers	2.1	0.7	[3, 2, 1, 2, 2, 2, 3, 2, 3, 1]
+adores	1.6	0.66332	[2, 1, 3, 2, 2, 1, 1, 1, 2, 1]
+adoring	2.6	0.66332	[2, 3, 3, 3, 1, 3, 3, 2, 3, 3]
+adoringly	2.4	0.8	[2, 3, 2, 3, 3, 3, 3, 1, 1, 3]
+adorn	0.9	0.53852	[1, 1, 1, 0, 2, 1, 1, 0, 1, 1]
+adorned	0.8	1.249	[1, 1, 0, 2, -1, 3, -1, 2, 1, 0]
+adorner	1.3	0.78102	[1, 1, 1, 2, 1, 3, 1, 2, 1, 0]
+adorners	0.9	0.9434	[2, 2, 0, 1, -1, 2, 1, 1, 0, 1]
+adorning	1.0	0.7746	[0, 0, 1, 1, 1, 2, 2, 1, 0, 2]
+adornment	1.3	0.78102	[1, 3, 1, 0, 2, 2, 1, 1, 1, 1]
+adornments	0.8	1.16619	[2, -1, 0, 0, 2, 1, 2, -1, 1, 2]
+adorns	0.5	1.56525	[3, -1, 1, 0, 2, -1, 3, -1, 0, -1]
+advanced	1.0	0.63246	[1, 0, 1, 1, 1, 0, 1, 2, 1, 2]
+advantage	1.0	0.63246	[1, 2, 1, 1, 2, 0, 1, 0, 1, 1]
+advantaged	1.4	0.91652	[1, 0, 3, 0, 1, 1, 2, 2, 2, 2]
+advantageous	1.5	0.67082	[2, 0, 2, 2, 2, 1, 1, 1, 2, 2]
+advantageously	1.9	0.53852	[2, 2, 2, 3, 2, 2, 2, 1, 1, 2]
+advantageousness	1.6	1.28062	[-2, 2, 3, 1, 2, 2, 2, 2, 2, 2]
+advantages	1.5	0.80623	[1, 0, 3, 1, 1, 1, 2, 2, 2, 2]
+advantaging	1.6	0.66332	[3, 1, 1, 2, 1, 1, 2, 2, 2, 1]
+adventure	1.3	0.45826	[1, 2, 1, 1, 2, 1, 1, 1, 1, 2]
+adventured	1.3	0.45826	[1, 2, 1, 2, 1, 2, 1, 1, 1, 1]
+adventurer	1.2	0.6	[1, 2, 0, 2, 1, 2, 1, 1, 1, 1]
+adventurers	0.9	0.9434	[0, 1, 0, 1, 0, 1, 0, 1, 3, 2]
+adventures	1.4	1.2	[2, 2, 1, 2, -2, 2, 2, 1, 2, 2]
+adventuresome	1.7	1.1	[0, 3, 0, 1, 2, 2, 3, 1, 2, 3]
+adventuresomeness	1.3	1.00499	[1, 0, 0, 2, 3, 2, 2, 0, 1, 2]
+adventuress	0.8	1.72047	[3, -1, 2, 2, 0, 0, 1, 2, -3, 2]
+adventuresses	1.4	1.11355	[1, 0, 0, 3, 2, 2, 3, 0, 1, 2]
+adventuring	2.3	0.78102	[2, 3, 2, 3, 1, 3, 3, 1, 2, 3]
+adventurism	1.5	0.67082	[1, 0, 2, 2, 2, 2, 1, 1, 2, 2]
+adventurist	1.4	0.4899	[1, 1, 2, 1, 2, 2, 2, 1, 1, 1]
+adventuristic	1.7	0.64031	[2, 1, 1, 2, 2, 1, 3, 2, 2, 1]
+adventurists	1.2	0.9798	[3, 1, 0, 0, 1, 2, 1, 0, 2, 2]
+adventurous	1.4	1.11355	[0, 1, 2, 1, 2, 0, 3, 2, 3, 0]
+adventurously	1.3	0.9	[0, 1, 2, 2, 1, 2, 1, 1, 0, 3]
+adventurousness	1.8	0.87178	[0, 1, 3, 2, 1, 3, 2, 2, 2, 2]
+adversarial	-1.5	0.92195	[-2, 0, -1, -3, -2, -2, 0, -1, -2, -2]
+adversaries	-1.0	0.63246	[-1, -1, -1, -1, 0, -2, -2, -1, -1, 0]
+adversary	-0.8	1.72047	[-3, -1, -2, -2, -2, 2, 1, -1, 2, -2]
+adversative	-1.2	0.74833	[-1, -1, -2, -1, -1, -1, -3, -1, 0, -1]
+adversatively	-0.1	1.37477	[0, -2, -1, 0, -1, -1, 1, 1, 3, -1]
+adversatives	-1.0	0.7746	[-1, -1, -2, -1, -2, 1, -1, -1, -1, -1]
+adverse	-1.5	0.80623	[-2, -2, -2, -1, -1, 0, -1, -3, -1, -2]
+adversely	-0.8	1.6	[-2, -2, 0, -2, -2, 2, -2, 2, -2, 0]
+adverseness	-0.6	1.35647	[-1, -2, -1, 2, -1, -2, -1, 2, -1, -1]
+adversities	-1.5	0.67082	[-2, -2, -1, -1, -2, 0, -2, -1, -2, -2]
+adversity	-1.8	0.6	[-3, -2, -1, -2, -2, -2, -1, -1, -2, -2]
+affected	-0.6	1.35647	[-1, -2, 0, -2, 0, 0, 2, -2, 1, -2]
+affection	2.4	0.8	[3, 2, 2, 3, 4, 1, 3, 2, 2, 2]
+affectional	1.9	1.04403	[3, 3, 2, 0, 2, 2, 2, 3, 2, 0]
+affectionally	1.5	0.92195	[1, 1, 3, 1, 1, 0, 2, 2, 3, 1]
+affectionate	1.9	1.13578	[1, 0, 3, 1, 3, 2, 2, 1, 2, 4]
+affectionately	2.2	0.87178	[4, 1, 1, 2, 2, 2, 3, 3, 2, 2]
+affectioned	1.8	0.4	[2, 2, 1, 2, 2, 1, 2, 2, 2, 2]
+affectionless	-2.0	0.44721	[-2, -1, -2, -2, -2, -2, -2, -2, -2, -3]
+affections	1.5	1.11803	[-1, 3, 2, 2, 1, 1, 2, 1, 3, 1]
+afflicted	-1.5	1.0247	[-1, -2, -3, -2, 1, -1, -1, -2, -2, -2]
+affronted	0.2	2.03961	[1, -2, 2, -2, -2, 4, 0, 2, 1, -2]
+aggravate	-2.5	0.80623	[-3, -3, -2, -3, -2, -4, -3, -2, -2, -1]
+aggravated	-1.9	1.04403	[-4, -3, -3, -1, -1, -1, -1, -2, -2, -1]
+aggravates	-1.9	0.83066	[-3, -2, -2, -2, -3, -1, -2, -2, 0, -2]
+aggravating	-1.2	0.9798	[-2, -2, -1, -2, -2, -1, 0, 1, -1, -2]
+aggress	-1.3	1.55242	[-2, -2, 2, -2, -1, -3, -3, -1, 1, -2]
+aggressed	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -2, -2, -1]
+aggresses	-0.5	1.43178	[-1, -2, -1, -1, -3, 0, -1, 1, 2, 1]
+aggressing	-0.6	1.28062	[-1, -2, -1, 0, -1, -2, 2, -2, 1, 0]
+aggression	-1.2	1.77764	[-2, -2, 1, 1, -4, 2, -2, -2, -2, -2]
+aggressions	-1.3	1.48661	[-1, -2, -2, -2, -2, -3, 1, -2, 2, -2]
+aggressive	-0.6	1.28062	[-2, 1, -2, -2, 0, -2, -1, 1, 1, 0]
+aggressively	-1.3	1.55242	[-1, -2, 3, -2, -3, -2, -1, -1, -2, -2]
+aggressiveness	-1.8	0.74833	[-1, -2, -1, -2, -2, -1, -3, -1, -3, -2]
+aggressivities	-1.4	1.28062	[-1, -1, -1, -2, 2, -2, -2, -2, -3, -2]
+aggressivity	-0.6	1.35647	[-3, -1, 1, 0, 0, 0, -3, -1, 1, 0]
+aggressor	-0.8	1.32665	[-2, 0, -1, 2, -2, -2, -1, -1, -2, 1]
+aggressors	-0.9	1.13578	[-2, -2, -1, -1, -1, 1, 1, 0, -2, -2]
+aghast	-1.9	1.04403	[-2, -3, -1, 0, -2, -1, -4, -2, -2, -2]
+agitate	-1.7	0.64031	[-2, -2, -3, -1, -1, -1, -2, -1, -2, -2]
+agitated	-2.0	0.63246	[-2, -2, -2, -2, -1, -3, -3, -2, -2, -1]
+agitatedly	-1.6	0.8	[-1, -2, -1, -3, -1, -3, -1, -1, -2, -1]
+agitates	-1.4	0.8	[-2, 0, -1, -2, -1, -1, -3, -1, -2, -1]
+agitating	-1.8	0.87178	[-2, -1, -1, -1, -2, -3, -1, -3, -3, -1]
+agitation	-1.0	1.09545	[-2, -1, 1, -1, -2, -1, -2, -1, 1, -2]
+agitational	-1.2	1.66132	[-3, -3, -2, 1, -1, -2, 0, 2, -1, -3]
+agitations	-1.3	1.18743	[-1, -2, -1, -3, -2, -3, 0, -1, 1, -1]
+agitative	-1.3	1.26886	[-2, -2, -1, -2, -1, -3, 1, -2, 1, -2]
+agitato	-0.1	1.13578	[1, 2, 0, 0, 0, 0, -2, 0, -2, 0]
+agitator	-1.4	0.8	[-1, -1, -1, -2, -1, -1, -2, -3, -2, 0]
+agitators	-2.1	0.9434	[-2, -3, -3, -2, -2, -1, -3, -2, 0, -3]
+agog	1.9	0.7	[2, 1, 3, 3, 2, 1, 2, 2, 1, 2]
+agonise	-2.1	0.9434	[-3, -3, -2, -3, -1, -3, -1, -3, -1, -1]
+agonised	-2.3	0.64031	[-2, -3, -3, -2, -2, -2, -2, -3, -1, -3]
+agonises	-2.4	0.91652	[-1, -4, -3, -3, -2, -2, -2, -3, -1, -3]
+agonising	-1.5	1.43178	[-3, -2, -3, -3, -1, 1, 0, 0, -1, -3]
+agonize	-2.3	0.9	[-2, -3, -1, -2, -2, -2, -4, -1, -3, -3]
+agonized	-2.2	1.249	[-2, -3, -3, -3, -3, -2, -1, -3, 1, -3]
+agonizes	-2.3	1.18743	[-1, -3, -4, -3, -3, -2, -1, -3, 0, -3]
+agonizing	-2.7	0.78102	[-3, -2, -2, -2, -4, -3, -3, -2, -4, -2]
+agonizingly	-2.3	1.48661	[-3, -1, -3, -4, -4, -2, -3, 1, -1, -3]
+agony	-1.8	1.16619	[-3, -1, -2, -4, -2, -1, 0, -3, -1, -1]
+agree	1.5	1.11803	[1, 0, 3, 1, 2, 1, 4, 1, 1, 1]
+agreeability	1.9	1.04403	[1, 1, 1, 3, 3, 2, 1, 2, 4, 1]
+agreeable	1.8	0.4	[2, 1, 2, 1, 2, 2, 2, 2, 2, 2]
+agreeableness	1.8	0.9798	[2, 3, 2, 1, 1, 1, 4, 1, 2, 1]
+agreeablenesses	1.3	0.45826	[2, 1, 1, 2, 1, 2, 1, 1, 1, 1]
+agreeably	1.6	0.4899	[1, 1, 2, 1, 1, 2, 2, 2, 2, 2]
+agreed	1.1	0.53852	[1, 1, 2, 1, 1, 2, 1, 0, 1, 1]
+agreeing	1.4	0.4899	[1, 1, 1, 1, 2, 1, 1, 2, 2, 2]
+agreement	2.2	0.74833	[2, 1, 1, 3, 3, 3, 2, 2, 2, 3]
+agreements	1.1	1.13578	[0, 1, 0, 1, 1, 2, 1, 0, 4, 1]
+agrees	0.8	1.4	[1, 1, 1, 1, 3, 1, -3, 1, 1, 1]
+alarm	-1.4	0.91652	[-1, -1, -2, -2, -2, -2, -1, 1, -2, -2]
+alarmed	-1.4	0.4899	[-2, -1, -2, -2, -1, -1, -1, -2, -1, -1]
+alarming	-0.5	1.62788	[-1, 1, -1, 1, -3, 1, -2, -3, 1, 1]
+alarmingly	-2.6	0.91652	[-3, -3, -4, -3, -2, -1, -3, -3, -1, -3]
+alarmism	-0.3	1.26886	[-2, 0, -2, -1, 0, 1, 1, -1, 2, -1]
+alarmists	-1.1	1.3	[-1, -2, -3, -2, -1, -2, 1, 1, 0, -2]
+alarms	-1.1	1.04403	[-2, 0, -2, -1, 0, 0, 0, -1, -2, -3]
+alas	-1.1	1.22066	[-1, -2, -1, 0, -1, 0, 1, -3, -1, -3]
+alert	1.2	0.87178	[1, 2, 0, 1, 0, 2, 2, 0, 2, 2]
+alienation	-1.1	1.51327	[-3, -2, -3, -1, -2, -1, 2, -1, 1, -1]
+alive	1.6	0.8	[1, 1, 2, 3, 3, 2, 1, 1, 1, 1]
+allergic	-1.2	0.4	[-1, -2, -1, -2, -1, -1, -1, -1, -1, -1]
+allow	0.9	0.83066	[0, 0, 0, 1, 2, 2, 1, 1, 2, 0]
+alone	-1.0	0.63246	[-2, -1, -1, -1, -2, -1, 0, -1, -1, 0]
+alright	1.0	0.7746	[0, 1, 0, 3, 1, 1, 1, 1, 1, 1]
+amaze	2.5	1.0247	[3, 2, 3, 4, 2, 3, 1, 4, 2, 1]
+amazed	2.2	1.07703	[1, 0, 3, 2, 2, 4, 3, 3, 2, 2]
+amazedly	2.1	0.53852	[2, 2, 2, 2, 3, 2, 2, 3, 1, 2]
+amazement	2.5	0.80623	[3, 3, 2, 4, 1, 2, 2, 3, 2, 3]
+amazements	2.2	0.87178	[3, 1, 1, 3, 3, 2, 1, 2, 3, 3]
+amazes	2.2	0.9798	[1, 0, 3, 2, 2, 3, 3, 3, 2, 3]
+amazing	2.8	0.87178	[1, 4, 3, 2, 4, 2, 3, 3, 3, 3]
+amazon	0.7	0.64031	[0, 1, 1, 0, 1, 0, 1, 0, 1, 2]
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+amazons	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, -1, 0]
+amazonstone	1.0	1.61245	[0, 0, 0, 0, 4, 4, 2, 0, 0, 0]
+amazonstones	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
+ambitious	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 2, 3, 1]
+ambivalent	0.5	0.92195	[0, 0, -1, 2, 1, 1, 1, -1, 1, 1]
+amor	3.0	0.63246	[3, 3, 2, 4, 3, 2, 4, 3, 3, 3]
+amoral	-1.6	0.66332	[-1, -2, 0, -2, -2, -2, -2, -2, -1, -2]
+amoralism	-0.7	1.34536	[-2, -1, -2, 0, 0, -3, 2, 0, -1, 0]
+amoralisms	-0.7	1.00499	[-2, 0, 1, -1, -2, -1, -1, 1, -1, -1]
+amoralities	-1.2	1.6	[-3, 0, 0, -2, 1, -1, 0, -4, -3, 0]
+amorality	-1.5	0.92195	[0, -1, -1, -2, -1, -3, -1, -3, -2, -1]
+amorally	-1.0	1.61245	[-2, 0, 1, -4, -1, 1, 1, -2, -2, -2]
+amoretti	0.2	0.4	[0, 0, 0, 1, 0, 0, 0, 0, 0, 1]
+amoretto	0.6	0.8	[0, 1, 0, 1, 0, 0, 2, 0, 0, 2]
+amorettos	0.3	0.64031	[0, 1, 0, 1, 0, 0, 0, 1, 1, -1]
+amorino	1.2	0.87178	[2, 1, 1, 0, 3, 1, 1, 0, 1, 2]
+amorist	1.6	1.0198	[3, 0, 0, 2, 2, 1, 3, 1, 2, 2]
+amoristic	1.0	1.67332	[1, 0, 2, 3, -1, 3, 1, 3, 0, -2]
+amorists	0.1	0.9434	[0, 2, 0, 0, 1, 0, -2, 0, 0, 0]
+amoroso	2.3	0.78102	[3, 1, 1, 2, 3, 3, 3, 3, 2, 2]
+amorous	1.8	0.9798	[3, 1, 2, 2, 1, 1, 3, 0, 2, 3]
+amorously	2.3	0.78102	[1, 1, 3, 2, 3, 3, 2, 3, 2, 3]
+amorousness	2.0	0.89443	[2, 3, 1, 2, 0, 2, 2, 3, 3, 2]
+amorphous	-0.2	0.4	[0, 0, 0, 0, 0, 0, -1, 0, 0, -1]
+amorphously	0.1	0.7	[-1, 0, 0, 0, 0, 0, 2, 0, 0, 0]
+amorphousness	0.3	0.45826	[0, 0, 0, 0, 0, 1, 1, 1, 0, 0]
+amort	-2.1	0.83066	[-3, -1, -2, -2, -2, -2, -2, -4, -1, -2]
+amortise	0.5	1.43178	[0, 1, 1, 0, -3, 2, 0, 0, 2, 2]
+amortised	-0.2	1.16619	[-1, -3, 0, 0, 0, 2, 0, 0, 0, 0]
+amortises	0.1	0.83066	[-1, -1, 0, 0, 0, 2, 1, 0, 0, 0]
+amortizable	0.5	1.0247	[2, 0, 1, 0, 1, 1, -2, 1, 0, 1]
+amortization	0.6	1.0198	[0, 0, 0, 0, 1, 0, 0, 0, 3, 2]
+amortizations	0.2	1.07703	[-1, 1, 0, 0, 1, 0, 2, 1, -2, 0]
+amortize	-0.1	1.04403	[0, 0, 0, 0, 2, -2, -1, 1, -1, 0]
+amortized	0.8	0.74833	[0, 2, 0, 0, 1, 1, 1, 0, 1, 2]
+amortizes	0.6	0.8	[0, 2, 0, 0, 1, 1, 0, 0, 0, 2]
+amortizing	0.8	1.249	[0, 3, 0, 0, 0, 0, 0, 0, 3, 2]
+amusable	0.7	1.18743	[2, 1, 1, 1, 1, 1, 2, -2, -1, 1]
+amuse	1.7	0.78102	[1, 2, 1, 1, 2, 1, 1, 3, 3, 2]
+amused	1.8	0.6	[1, 2, 2, 2, 2, 2, 1, 2, 3, 1]
+amusedly	2.2	0.74833	[3, 3, 2, 2, 3, 2, 2, 3, 1, 1]
+amusement	1.5	1.11803	[3, 2, 3, 1, 2, 2, -1, 1, 1, 1]
+amusements	1.5	1.0247	[2, 1, 2, 1, 2, 2, 3, -1, 2, 1]
+amuser	1.1	1.7	[2, 1, -3, 2, 2, 3, -1, 1, 2, 2]
+amusers	1.3	0.45826	[1, 1, 2, 1, 2, 1, 2, 1, 1, 1]
+amuses	1.7	0.64031	[1, 2, 1, 2, 2, 2, 1, 2, 3, 1]
+amusia	0.3	1.48661	[0, -1, 1, -1, 2, 2, -1, -1, -1, 3]
+amusias	-0.4	0.66332	[-1, 0, 0, 1, 0, 0, -1, -1, -1, -1]
+amusing	1.6	0.91652	[2, 2, 2, -1, 2, 2, 1, 2, 2, 2]
+amusingly	0.8	1.249	[1, 2, 1, 1, 1, 2, 2, -2, -1, 1]
+amusingness	1.8	0.6	[1, 2, 3, 2, 1, 2, 2, 1, 2, 2]
+amusive	1.7	1.1	[3, 1, 3, 1, 2, 2, 2, 2, -1, 2]
+anger	-2.7	1.18743	[-1, -2, -3, -2, -4, -4, -2, -1, -4, -4]
+angered	-2.3	0.78102	[-2, -3, -2, -4, -2, -2, -3, -2, -2, -1]
+angering	-2.2	0.6	[-3, -2, -1, -3, -2, -2, -3, -2, -2, -2]
+angerly	-1.9	0.53852	[-2, -2, -1, -1, -3, -2, -2, -2, -2, -2]
+angers	-2.3	0.9	[-3, -1, -2, -3, -2, -2, -4, -1, -3, -2]
+angrier	-2.3	0.64031	[-2, -3, -2, -3, -1, -3, -2, -3, -2, -2]
+angriest	-3.1	0.83066	[-4, -3, -2, -2, -2, -4, -3, -4, -4, -3]
+angrily	-1.8	0.4	[-2, -1, -2, -2, -2, -1, -2, -2, -2, -2]
+angriness	-1.7	0.64031	[-2, 0, -2, -2, -1, -2, -2, -2, -2, -2]
+angry	-2.3	0.9	[-2, -2, -1, -3, -1, -2, -4, -2, -3, -3]
+anguish	-2.9	0.83066	[-3, -3, -2, -3, -4, -1, -3, -3, -4, -3]
+anguished	-1.8	1.4	[-3, -4, -1, -3, -2, -1, -1, 1, -1, -3]
+anguishes	-2.1	1.44568	[-4, -4, -2, -3, 1, -2, -1, -1, -2, -3]
+anguishing	-2.7	0.9	[-2, -2, -1, -3, -2, -4, -4, -3, -3, -3]
+animosity	-1.9	1.75784	[-2, -3, -3, -3, -2, 2, 1, -3, -3, -3]
+annoy	-1.9	0.53852	[-2, -2, -1, -2, -2, -1, -2, -2, -2, -3]
+annoyance	-1.3	1.55242	[-2, -3, -2, -2, -1, 1, -3, -2, 2, -1]
+annoyances	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -3, -1, -2, -2]
+annoyed	-1.6	1.11355	[-3, -1, 1, -3, -1, -1, -2, -2, -2, -2]
+annoyer	-2.2	0.87178	[-3, -2, -1, -3, -2, -4, -2, -1, -2, -2]
+annoyers	-1.5	1.0247	[-2, -1, -2, -3, -2, -1, -1, -2, 1, -2]
+annoying	-1.7	0.64031	[-1, -2, -1, -2, -1, -1, -2, -2, -3, -2]
+annoys	-1.8	0.6	[-1, -2, -3, -2, -2, -2, -1, -2, -1, -2]
+antagonism	-1.9	1.04403	[-1, -1, -3, -2, -4, -2, -2, 0, -2, -2]
+antagonisms	-1.2	1.53623	[0, -2, -2, -2, -2, -2, 3, -2, -1, -2]
+antagonist	-1.9	0.7	[-3, -1, -2, -3, -2, -2, -1, -2, -2, -1]
+antagonistic	-1.7	0.9	[-2, -2, -2, 1, -2, -2, -2, -2, -2, -2]
+antagonistically	-2.2	0.87178	[-2, -3, -4, -2, -2, -3, -2, -2, -1, -1]
+antagonists	-1.7	0.64031	[-2, -1, -1, -2, -1, -2, -2, -3, -1, -2]
+antagonize	-2.0	0.44721	[-2, -2, -2, -3, -2, -1, -2, -2, -2, -2]
+antagonized	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -2, -1, -1, -2]
+antagonizes	-0.5	1.9105	[-2, 4, -2, -2, 1, 0, -2, 1, -1, -2]
+antagonizing	-2.7	0.64031	[-4, -2, -2, -3, -2, -3, -3, -2, -3, -3]
+anti	-1.3	0.78102	[0, -2, -3, -1, -1, -2, -1, -1, -1, -1]
+anticipation	0.4	1.28062	[1, 1, -1, 0, -1, 1, 1, 2, -2, 2]
+anxieties	-0.6	1.85472	[-2, -3, -3, -2, -1, 2, -1, 1, 1, 2]
+anxiety	-0.7	2.1	[-2, -2, -2, -3, 3, -1, -3, 2, 2, -1]
+anxious	-1.0	0.44721	[-1, -2, -1, -1, 0, -1, -1, -1, -1, -1]
+anxiously	-0.9	0.83066	[-1, -1, -2, -1, -1, -1, -1, 0, 1, -2]
+anxiousness	-1.0	1.48324	[-2, -1, -1, -1, -1, -2, 3, -3, -1, -1]
+aok	2.0	0.89443	[2, 3, 2, 1, 2, 1, 1, 4, 2, 2]
+apathetic	-1.2	0.87178	[-1, -1, 0, -2, -2, -1, -1, 0, -3, -1]
+apathetically	-0.4	1.28062	[-1, -1, 0, -1, -2, 2, -1, -1, 2, -1]
+apathies	-0.6	1.0198	[-1, -1, -1, -2, 0, 1, -1, -2, 1, 0]
+apathy	-1.2	1.32665	[-2, -2, -1, 1, -1, -3, -1, 1, -1, -3]
+apeshit	-0.9	2.21133	[-4, -3, 2, -3, -2, -3, 1, 0, 2, 1]
+apocalyptic	-3.4	0.66332	[-4, -2, -3, -4, -3, -4, -4, -3, -3, -4]
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+apologised	0.4	0.91652	[-1, 0, 2, 0, 0, 1, 0, 2, 0, 0]
+apologises	0.8	1.07703	[2, 0, 2, 0, 0, 1, 0, 3, 0, 0]
+apologising	0.2	1.6	[0, -1, -1, 2, 2, 1, -2, -1, 3, -1]
+apologize	0.4	0.8	[1, -1, 0, 1, 1, 1, -1, 1, 0, 1]
+apologized	1.3	0.64031	[1, 1, 1, 2, 0, 2, 1, 2, 2, 1]
+apologizes	1.5	0.80623	[2, 1, 1, 2, 0, 2, 1, 2, 3, 1]
+apologizing	-0.3	1.34536	[1, 2, -1, 1, -1, 0, -3, 0, -1, -1]
+apology	0.2	1.249	[1, 1, 1, 1, -1, 1, -1, -1, -2, 2]
+appall	-2.4	0.66332	[-3, -2, -2, -3, -2, -3, -1, -3, -2, -3]
+appalled	-2.0	0.63246	[-3, -2, -3, -2, -2, -1, -1, -2, -2, -2]
+appalling	-1.5	1.5	[-2, -4, 1, -1, 1, -1, -2, -3, -2, -2]
+appallingly	-2.0	1.67332	[-3, -2, 0, -2, 2, -3, -4, -3, -2, -3]
+appalls	-1.9	1.37477	[0, -3, -2, -3, -3, -2, -1, -3, 1, -3]
+appease	1.1	0.9434	[1, 1, 1, -1, 2, 0, 1, 2, 2, 2]
+appeased	0.9	0.53852	[0, 1, 1, 1, 1, 1, 0, 1, 2, 1]
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+appeasing	1.0	1.09545	[1, 2, -1, 1, 2, 1, 2, 2, 1, -1]
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+applauded	1.5	0.5	[2, 2, 1, 2, 2, 2, 1, 1, 1, 1]
+applauding	2.1	0.83066	[2, 2, 4, 1, 2, 2, 2, 1, 2, 3]
+applauds	1.4	0.66332	[1, 1, 2, 1, 3, 1, 1, 1, 2, 1]
+applause	1.8	0.6	[2, 1, 1, 2, 3, 2, 1, 2, 2, 2]
+appreciate	1.7	0.78102	[2, 1, 2, 1, 1, 3, 1, 2, 3, 1]
+appreciated	2.3	0.78102	[2, 1, 3, 2, 3, 4, 2, 2, 2, 2]
+appreciates	2.3	0.9	[3, 1, 3, 1, 2, 4, 2, 3, 2, 2]
+appreciating	1.9	0.7	[1, 1, 2, 2, 2, 2, 1, 3, 2, 3]
+appreciation	2.3	0.9	[3, 3, 2, 1, 1, 3, 3, 1, 3, 3]
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+appreciative	2.6	0.8	[3, 3, 3, 2, 1, 3, 4, 2, 2, 3]
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+appreciativeness	1.6	0.8	[2, 1, 1, 2, 1, 1, 3, 3, 1, 1]
+appreciator	2.6	0.8	[2, 3, 2, 3, 3, 2, 1, 3, 4, 3]
+appreciators	1.5	0.80623	[1, 3, 1, 3, 1, 1, 2, 1, 1, 1]
+appreciatory	1.7	0.78102	[1, 2, 1, 3, 1, 3, 2, 2, 1, 1]
+apprehensible	1.1	1.04403	[2, 0, -1, 3, 1, 2, 1, 1, 1, 1]
+apprehensibly	-0.2	1.16619	[0, 0, -1, 2, -1, 2, -1, -1, -1, -1]
+apprehension	-2.1	0.83066	[-1, -2, -2, -1, -2, -3, -3, -3, -1, -3]
+apprehensions	-0.9	1.04403	[-1, -1, -1, -1, -2, -2, -1, -1, -1, 2]
+apprehensively	-0.3	1.18743	[-1, -1, -1, 0, 1, -2, -1, 1, -1, 2]
+apprehensiveness	-0.7	0.9	[-1, 1, -1, -1, 1, -1, -2, -1, -1, -1]
+approval	2.1	0.53852	[2, 2, 2, 2, 2, 1, 3, 3, 2, 2]
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+approves	1.7	0.64031	[1, 1, 1, 2, 3, 2, 2, 2, 2, 1]
+ardent	2.1	0.7	[3, 3, 2, 2, 3, 1, 2, 2, 1, 2]
+arguable	-1.0	0.63246	[-1, -1, -2, -1, -1, -2, 0, 0, -1, -1]
+arguably	-1.0	1.09545	[0, -2, 0, -2, 0, 1, -1, -2, -2, -2]
+argue	-1.4	0.66332	[-1, -2, -1, -3, -2, -1, -1, -1, -1, -1]
+argued	-1.5	0.5	[-2, -2, -1, -1, -1, -1, -2, -2, -2, -1]
+arguer	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -1]
+arguers	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -1]
+argues	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -1]
+arguing	-2.0	0.63246	[-3, -3, -1, -1, -2, -2, -2, -2, -2, -2]
+argument	-1.5	0.80623	[-3, -1, -1, -1, -1, -2, 0, -2, -2, -2]
+argumentative	-1.5	0.67082	[-3, -2, -1, -1, -1, -1, -1, -2, -2, -1]
+argumentatively	-1.8	0.9798	[-4, -2, -1, -1, -3, -1, -2, -2, -1, -1]
+argumentive	-1.5	0.80623	[-3, -2, -2, -1, 0, -1, -1, -1, -2, -2]
+arguments	-1.7	0.64031	[-1, -1, -2, -2, -2, -3, -2, -1, -1, -2]
+arrest	-1.4	1.42829	[-1, 0, -1, 0, -2, -3, 0, -4, -3, 0]
+arrested	-2.1	1.04403	[-2, -2, -2, -1, -1, -4, -1, -4, -2, -2]
+arrests	-1.9	0.83066	[-4, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+arrogance	-2.4	0.66332	[-3, -2, -2, -3, -1, -2, -3, -3, -2, -3]
+arrogances	-1.9	0.53852	[-1, -2, -3, -2, -2, -2, -2, -1, -2, -2]
+arrogant	-2.2	0.6	[-2, -2, -2, -3, -2, -3, -3, -2, -1, -2]
+arrogantly	-1.8	1.4	[-3, -2, 2, -3, -1, -3, -2, -2, -2, -2]
+ashamed	-2.1	1.3	[-3, -3, -3, -2, -2, 1, -2, -4, -1, -2]
+ashamedly	-1.7	0.64031	[-2, -2, -2, -1, -2, -3, -1, -2, -1, -1]
+ass	-2.5	1.43178	[-4, -1, -2, -1, -3, 0, -2, -4, -4, -4]
+assassination	-2.9	0.9434	[-2, -4, -4, -3, -3, -4, -2, -3, -3, -1]
+assassinations	-2.7	1.34536	[-4, -2, -3, -2, -3, -1, -4, -4, 0, -4]
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+assaulted	-2.4	1.28062	[-3, -3, 1, -3, -3, -3, -1, -3, -3, -3]
+assaulting	-2.3	1.1	[-4, -3, -2, -1, -2, -1, -1, -4, -3, -2]
+assaultive	-2.8	0.87178	[-3, -4, -2, -4, -3, -2, -3, -1, -3, -3]
+assaults	-2.5	0.92195	[-1, -3, -3, -3, -4, -3, -1, -2, -2, -3]
+asset	1.5	0.80623	[2, 1, 1, 3, 2, 0, 2, 2, 1, 1]
+assets	0.7	1.00499	[0, 0, 1, 3, 0, 1, 0, 0, 2, 0]
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+assurance	1.4	0.4899	[1, 1, 2, 2, 1, 1, 1, 2, 2, 1]
+assurances	1.4	0.4899	[2, 2, 1, 1, 1, 2, 2, 1, 1, 1]
+assure	1.4	0.4899	[1, 1, 1, 1, 2, 1, 1, 2, 2, 2]
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+assuredly	1.6	0.66332	[1, 1, 1, 3, 2, 2, 2, 1, 2, 1]
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+assuring	1.6	0.66332	[1, 2, 2, 3, 1, 1, 1, 1, 2, 2]
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+astonished	1.6	0.8	[3, 1, 0, 2, 2, 1, 2, 2, 1, 2]
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+astounded	1.8	0.9798	[1, 3, 0, 1, 2, 2, 3, 2, 1, 3]
+astounding	1.8	1.4	[3, 4, 2, 0, 1, 2, -1, 3, 2, 2]
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+attachment	1.2	0.9798	[2, 0, 1, 2, 3, 1, 1, 2, 0, 0]
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+attacked	-2.0	1.78885	[-2, 3, -2, -2, -3, -3, -3, -4, -2, -2]
+attacker	-2.7	0.9	[-2, -3, -2, -1, -3, -3, -4, -4, -2, -3]
+attackers	-2.7	0.64031	[-3, -3, -3, -2, -3, -3, -4, -2, -2, -2]
+attacking	-2.0	0.89443	[-3, -1, -1, -3, -3, -1, -3, -1, -2, -2]
+attacks	-1.9	0.9434	[-2, -2, 0, -2, -2, -2, -1, -4, -2, -2]
+attract	1.5	0.92195	[1, 3, 1, 1, 3, 1, 1, 2, 0, 2]
+attractancy	0.9	0.7	[1, 0, 2, 1, 0, 2, 1, 1, 0, 1]
+attractant	1.3	0.9	[0, 1, 0, 1, 1, 2, 3, 2, 1, 2]
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+attracted	1.8	0.6	[1, 3, 1, 2, 2, 2, 2, 2, 2, 1]
+attracting	2.1	0.83066	[3, 1, 2, 2, 3, 1, 1, 3, 2, 3]
+attraction	2.0	0.7746	[2, 2, 1, 1, 2, 3, 3, 2, 3, 1]
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+attractive	1.9	0.53852	[2, 2, 2, 1, 3, 2, 1, 2, 2, 2]
+attractively	2.2	0.6	[3, 2, 2, 3, 2, 2, 2, 3, 1, 2]
+attractiveness	1.8	1.16619	[3, 2, 2, 1, 4, 2, 0, 0, 2, 2]
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+attractor	1.2	1.16619	[1, 1, 2, 2, 2, -2, 2, 1, 2, 1]
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+attracts	1.7	1.00499	[2, 1, 2, 0, 2, 4, 2, 1, 1, 2]
+audacious	0.9	2.02237	[3, -1, -2, 2, 1, 2, -3, 2, 2, 3]
+authority	0.3	0.64031	[0, 0, 0, 1, 0, 0, 2, 0, 0, 0]
+aversion	-1.9	1.04403	[-3, -3, -1, -2, 0, -3, -1, -2, -1, -3]
+aversions	-1.1	1.13578	[-2, -1, -2, -2, -2, 1, -1, -2, 1, -1]
+aversive	-1.6	0.66332	[-2, -1, -1, -1, -2, -2, -1, -2, -3, -1]
+aversively	-0.8	1.53623	[-3, -1, -2, -1, 1, -2, 2, -2, 1, -1]
+avert	-0.7	0.78102	[-1, 0, -2, -1, -1, 1, -1, 0, -1, -1]
+averted	-0.3	1.00499	[-1, 1, 0, 0, 1, 0, -2, 0, 0, -2]
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+avoidance	-1.7	0.45826	[-2, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+avoidances	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -2, -1, -1]
+avoided	-1.4	0.4899	[-2, -1, -2, -1, -1, -1, -2, -1, -2, -1]
+avoider	-1.8	0.6	[-2, -1, -3, -1, -2, -2, -2, -1, -2, -2]
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+awardees	1.2	0.74833	[1, 1, 1, 1, 0, 1, 1, 1, 3, 2]
+awarder	0.9	1.04403	[2, 0, 1, 3, 0, 2, 1, 0, 0, 0]
+awarders	1.3	1.18743	[2, 1, 0, 2, 2, 0, 0, 4, 1, 1]
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+axed	-1.3	0.78102	[-1, -2, 0, -3, -1, -2, -1, -1, -1, -1]
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+bad	-2.5	0.67082	[-3, -2, -4, -3, -2, -2, -3, -2, -2, -2]
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+bailout	-0.4	1.35647	[-1, 0, 0, 2, -2, -1, -2, 2, -1, -1]
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+bamboozled	-1.5	1.11803	[-1, 0, -2, -4, -2, -1, -2, -1, 0, -2]
+bamboozles	-1.5	1.0247	[-1, 0, -2, -4, -2, -1, -2, -1, -1, -1]
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+bashfully	0.2	0.9798	[0, 0, 0, -1, 1, 1, 1, 1, -2, 1]
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+bastard	-2.5	0.67082	[-2, -4, -2, -3, -2, -2, -3, -3, -2, -2]
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+bastardised	-2.3	0.9	[-3, -2, -3, -1, -2, -3, -4, -1, -2, -2]
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+bastardising	-2.6	0.8	[-3, -2, -3, -2, -2, -1, -3, -4, -3, -3]
+bastardization	-2.4	1.28062	[-1, -3, -4, -4, -2, -2, -2, 0, -2, -4]
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+bastardize	-2.4	0.66332	[-2, -2, -3, -2, -2, -3, -4, -2, -2, -2]
+bastardized	-2.0	0.7746	[-2, -1, -1, -2, -3, -2, -3, -2, -1, -3]
+bastardizes	-1.8	0.87178	[-2, -1, -1, -2, -2, -2, -3, -3, 0, -2]
+bastardizing	-2.3	0.9	[-2, -2, -1, -4, -3, -2, -1, -2, -3, -3]
+bastardly	-2.7	0.64031	[-3, -3, -2, -2, -3, -2, -2, -4, -3, -3]
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+battlefront	-1.2	0.87178	[-1, 0, -2, -1, 0, -3, -1, -2, -1, -1]
+battlefronts	-0.8	1.16619	[0, 0, -2, -1, 0, -3, -1, 1, -2, 0]
+battleground	-1.7	0.78102	[-2, 0, -2, -2, -1, -2, -2, -3, -1, -2]
+battlegrounds	-0.6	1.35647	[2, -2, 0, -1, 0, -2, -2, -2, 0, 1]
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+battlers	-0.2	0.9798	[-1, 0, 2, -2, 0, 0, 0, -1, 0, 0]
+battles	-1.6	0.4899	[-1, -1, -2, -1, -2, -2, -2, -1, -2, -2]
+battleship	-0.1	1.3	[2, -3, -1, -1, 0, 0, 1, 1, 0, 0]
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+battling	-1.1	1.04403	[0, -1, -2, -2, -1, 1, -2, 0, -2, -2]
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+beatific	1.8	1.6	[3, 0, 2, 4, -2, 2, 2, 2, 2, 3]
+beating	-2.0	0.63246	[-2, -3, -2, -2, -1, -1, -2, -3, -2, -2]
+beaut	1.6	1.2	[2, 2, 2, 0, 1, -1, 2, 3, 3, 2]
+beauteous	2.5	1.0247	[2, 1, 4, 3, 3, 2, 1, 4, 2, 3]
+beauteously	2.6	0.8	[2, 3, 3, 3, 2, 1, 3, 4, 2, 3]
+beauteousness	2.7	1.00499	[1, 3, 4, 3, 4, 1, 2, 3, 3, 3]
+beautician	1.2	0.9798	[0, 0, 3, 2, 2, 0, 1, 1, 1, 2]
+beauticians	0.4	0.66332	[0, 1, 0, 0, 0, 0, 1, 0, 2, 0]
+beauties	2.4	0.8	[2, 3, 3, 3, 3, 1, 2, 1, 3, 3]
+beautification	1.9	0.7	[2, 2, 2, 1, 2, 1, 3, 1, 2, 3]
+beautifications	2.4	0.8	[3, 2, 3, 3, 1, 3, 2, 3, 1, 3]
+beautified	2.1	0.7	[2, 2, 3, 1, 2, 2, 3, 1, 2, 3]
+beautifier	1.7	0.64031	[2, 1, 2, 1, 2, 1, 3, 1, 2, 2]
+beautifiers	1.7	0.78102	[3, 3, 1, 2, 1, 2, 2, 1, 1, 1]
+beautifies	1.8	0.74833	[2, 1, 2, 1, 2, 1, 3, 1, 2, 3]
+beautiful	2.9	0.7	[2, 3, 2, 3, 2, 3, 4, 4, 3, 3]
+beautifuler	2.1	0.83066	[2, 0, 2, 2, 3, 2, 2, 2, 3, 3]
+beautifulest	2.6	0.8	[3, 3, 3, 3, 2, 2, 4, 2, 1, 3]
+beautifully	2.7	0.64031	[3, 3, 2, 2, 3, 3, 2, 2, 4, 3]
+beautifulness	2.6	0.8	[3, 3, 3, 2, 3, 4, 3, 2, 2, 1]
+beautify	2.3	0.45826	[2, 3, 3, 2, 2, 3, 2, 2, 2, 2]
+beautifying	2.3	0.78102	[1, 2, 1, 3, 2, 2, 3, 3, 3, 3]
+beauts	1.7	0.78102	[1, 2, 0, 3, 1, 2, 2, 2, 2, 2]
+beauty	2.8	0.74833	[3, 3, 2, 3, 4, 4, 2, 2, 3, 2]
+belittle	-1.9	0.53852	[-2, -2, -2, -1, -2, -2, -1, -2, -3, -2]
+belittled	-2.0	1.0	[-3, -2, -3, -3, -2, -3, -1, -1, -2, 0]
+beloved	2.3	0.45826	[2, 2, 3, 2, 2, 2, 2, 3, 3, 2]
+benefic	1.4	0.4899	[2, 2, 1, 1, 1, 2, 2, 1, 1, 1]
+benefice	0.4	0.66332	[0, 2, 0, 1, 0, 0, 1, 0, 0, 0]
+beneficed	1.1	0.7	[1, 1, 1, 0, 2, 0, 1, 1, 2, 2]
+beneficence	2.8	0.87178	[1, 4, 3, 4, 2, 2, 3, 3, 3, 3]
+beneficences	1.5	0.67082	[1, 1, 2, 2, 1, 1, 1, 3, 2, 1]
+beneficent	2.3	0.45826	[3, 2, 3, 2, 2, 2, 2, 3, 2, 2]
+beneficently	2.2	0.6	[3, 2, 3, 3, 2, 2, 1, 2, 2, 2]
+benefices	1.1	0.83066	[1, 1, 1, 0, 1, 0, 1, 1, 2, 3]
+beneficial	1.9	0.53852	[2, 2, 1, 2, 2, 1, 3, 2, 2, 2]
+beneficially	2.4	0.8	[3, 3, 2, 2, 2, 1, 3, 4, 2, 2]
+beneficialness	1.7	0.64031	[2, 1, 2, 2, 1, 1, 2, 2, 1, 3]
+beneficiaries	1.8	1.16619	[0, 1, 2, 1, 3, 4, 3, 1, 2, 1]
+beneficiary	2.1	0.83066	[1, 3, 2, 2, 2, 1, 3, 3, 1, 3]
+beneficiate	1.0	1.18322	[0, 0, 1, 3, 1, 0, 2, 0, 3, 0]
+beneficiation	0.4	1.0198	[2, 2, 0, -1, 1, 0, -1, 0, 0, 1]
+benefit	2.0	0.63246	[2, 3, 1, 2, 2, 3, 2, 1, 2, 2]
+benefits	1.6	0.4899	[2, 2, 2, 1, 2, 1, 2, 2, 1, 1]
+benefitted	1.7	0.64031	[2, 2, 1, 2, 2, 2, 2, 2, 0, 2]
+benefitting	1.9	0.7	[1, 2, 2, 3, 1, 1, 2, 3, 2, 2]
+benevolence	1.7	1.1	[2, 1, 3, 2, 2, 1, 2, 2, -1, 3]
+benevolences	1.9	1.64012	[3, 2, -1, -1, 3, 1, 3, 4, 2, 3]
+benevolent	2.7	0.78102	[2, 2, 3, 2, 4, 2, 3, 2, 4, 3]
+benevolently	1.4	1.11355	[2, 1, 2, 2, 1, -1, 2, 3, 0, 2]
+benevolentness	1.2	1.249	[2, 2, 1, -1, 2, 2, 3, -1, 1, 1]
+benign	1.3	0.9	[1, 3, 2, 2, 1, 1, 2, 0, 0, 1]
+benignancy	0.6	1.2	[2, -1, -2, 1, 0, 1, 1, 2, 1, 1]
+benignant	2.2	0.9798	[2, 2, 2, 2, 2, 2, 4, 0, 3, 3]
+benignantly	1.1	1.3	[3, 2, 3, 0, 1, 1, -1, 2, 0, 0]
+benignities	0.9	0.9434	[-1, 2, 1, 0, 1, 1, 2, 2, 1, 0]
+benignity	1.3	1.18743	[2, -2, 2, 2, 2, 1, 2, 1, 1, 2]
+benignly	0.2	1.07703	[0, -1, 1, 1, 1, 0, 2, 0, -2, 0]
+bereave	-2.1	1.13578	[0, -2, -2, -3, -3, -4, -3, -2, -1, -1]
+bereaved	-2.1	0.9434	[-2, -2, -2, -1, -2, -1, -4, -1, -3, -3]
+bereaves	-1.9	1.22066	[0, -3, 0, -1, -3, -2, -3, -1, -3, -3]
+bereaving	-1.3	1.84662	[-3, -4, -3, 1, -2, 0, -3, -1, 1, 1]
+best	3.2	0.6	[2, 4, 4, 3, 4, 3, 3, 3, 3, 3]
+betray	-3.2	0.6	[-3, -4, -4, -3, -2, -3, -4, -3, -3, -3]
+betrayal	-2.8	0.74833	[-3, -4, -4, -2, -3, -2, -3, -3, -2, -2]
+betrayed	-3.0	0.63246	[-2, -3, -3, -3, -4, -4, -3, -3, -2, -3]
+betraying	-2.5	0.67082	[-2, -2, -3, -2, -3, -2, -4, -2, -2, -3]
+betrays	-2.5	0.67082	[-2, -3, -3, -2, -2, -2, -4, -2, -3, -2]
+better	1.9	0.7	[2, 1, 2, 1, 1, 3, 2, 2, 3, 2]
+bias	-0.4	1.11355	[-1, -2, 0, -2, -1, 1, -1, 1, 0, 1]
+biased	-1.1	0.83066	[-2, -2, -1, -1, -1, -1, -1, 1, -2, -1]
+bitch	-2.8	0.87178	[-1, -4, -2, -4, -3, -2, -3, -3, -3, -3]
+bitched	-2.6	1.0198	[-1, -3, -2, -3, -2, -1, -4, -3, -3, -4]
+bitcheries	-2.3	0.78102	[-2, -2, -2, -4, -2, -2, -3, -1, -3, -2]
+bitchery	-2.7	1.18743	[-2, -2, -4, -2, -4, -4, -1, -1, -3, -4]
+bitches	-2.9	0.9434	[-2, -1, -3, -3, -2, -4, -4, -3, -3, -4]
+bitchier	-2.0	0.63246	[-2, -3, -1, -2, -3, -1, -2, -2, -2, -2]
+bitchiest	-3.0	0.7746	[-2, -4, -2, -3, -4, -3, -3, -4, -2, -3]
+bitchily	-2.6	1.11355	[-4, -4, -2, -2, -1, -4, -1, -2, -3, -3]
+bitchiness	-2.6	0.66332	[-3, -3, -2, -2, -3, -3, -1, -3, -3, -3]
+bitching	-1.1	1.64012	[-2, 2, -2, -1, 2, -1, -2, -2, -3, -2]
+bitchy	-2.3	1.00499	[-4, -1, -2, -3, -3, -2, -1, -1, -3, -3]
+bitter	-1.8	0.4	[-2, -2, -2, -1, -2, -2, -1, -2, -2, -2]
+bitterbrush	-0.2	0.74833	[0, 0, 0, 0, -2, 1, 0, 0, -1, 0]
+bitterbrushes	-0.6	0.8	[-1, 0, -2, -1, -2, 0, 0, 0, 0, 0]
+bittered	-1.8	1.07703	[-1, -1, -3, -1, -2, -4, -2, 0, -2, -2]
+bitterer	-1.9	1.04403	[-1, -2, -3, -1, -1, -4, -3, -1, -2, -1]
+bitterest	-2.3	1.41774	[-4, -4, -2, -1, 1, -2, -3, -3, -2, -3]
+bittering	-1.2	0.87178	[0, 0, -1, -2, 0, -2, -1, -2, -2, -2]
+bitterish	-1.6	0.8	[0, -2, -1, -1, -2, -2, -2, -1, -3, -2]
+bitterly	-2.0	0.63246	[-2, -2, -1, -1, -2, -2, -3, -2, -2, -3]
+bittern	-0.2	0.6	[0, 0, -2, 0, 0, 0, 0, 0, 0, 0]
+bitterness	-1.7	0.45826	[-2, -2, -1, -2, -1, -2, -1, -2, -2, -2]
+bitterns	-0.4	1.11355	[0, 0, 0, -3, 0, 0, 0, 1, 0, -2]
+bitterroots	-0.2	0.4	[0, 0, 0, -1, -1, 0, 0, 0, 0, 0]
+bitters	-0.4	0.4899	[-1, -1, -1, 0, 0, 0, 0, -1, 0, 0]
+bittersweet	-0.3	0.64031	[0, -1, 0, 0, 0, 0, 0, 0, -2, 0]
+bittersweetness	-0.6	0.91652	[0, 0, 0, -2, 0, -2, 0, 0, -2, 0]
+bittersweets	-0.2	0.9798	[-2, 1, 0, 0, 0, -2, 0, 0, 0, 1]
+bitterweeds	-0.5	0.67082	[0, -2, 0, -1, -1, 0, 0, -1, 0, 0]
+bizarre	-1.3	1.00499	[-2, 0, 0, -2, 0, -1, -3, -2, -1, -2]
+blah	-0.4	1.49666	[-2, -1, -1, -1, -1, -1, -1, 3, 2, -1]
+blam	-0.2	1.16619	[-1, 0, 0, -1, -1, -2, -1, 1, 2, 1]
+blamable	-1.8	0.4	[-2, -2, -2, -2, -1, -1, -2, -2, -2, -2]
+blamably	-1.8	0.4	[-2, -2, -2, -2, -1, -1, -2, -2, -2, -2]
+blame	-1.4	1.42829	[-4, -2, -2, -1, -1, -1, -2, 2, -2, -1]
+blamed	-2.1	0.53852	[-2, -2, -2, -2, -3, -2, -2, -2, -3, -1]
+blameful	-1.7	0.45826	[-2, -2, -2, -2, -2, -2, -1, -1, -2, -1]
+blamefully	-1.6	0.66332	[-1, -2, -1, -1, -2, -1, -1, -2, -2, -3]
+blameless	0.7	1.73494	[3, 1, 2, 3, -2, 1, -1, 1, 1, -2]
+blamelessly	0.9	1.37477	[2, 0, 2, 0, 1, -1, 1, 4, 0, 0]
+blamelessness	0.6	1.35647	[0, 2, 1, 2, 1, 0, 1, -3, 1, 1]
+blamer	-2.1	0.83066	[-2, -2, -1, -2, -3, -3, -3, -1, -1, -3]
+blamers	-2.0	0.63246	[-3, -2, -2, -3, -1, -2, -2, -1, -2, -2]
+blames	-1.7	0.45826	[-2, -2, -1, -2, -2, -2, -2, -1, -1, -2]
+blameworthiness	-1.6	0.66332	[-2, -2, -1, -2, -2, -1, -3, -1, -1, -1]
+blameworthy	-2.3	0.78102	[-3, -3, -2, -2, -2, -1, -1, -3, -3, -3]
+blaming	-2.2	0.6	[-2, -3, -1, -3, -2, -2, -3, -2, -2, -2]
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+blessed	2.9	0.3	[2, 3, 3, 3, 3, 3, 3, 3, 3, 3]
+blesseder	2.0	0.63246	[3, 3, 2, 2, 1, 1, 2, 2, 2, 2]
+blessedest	2.8	0.87178	[2, 4, 1, 4, 3, 3, 2, 3, 3, 3]
+blessedly	1.7	1.1	[2, 2, 1, -1, 3, 2, 3, 1, 2, 2]
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+blesser	2.6	0.66332	[1, 3, 2, 3, 3, 3, 2, 3, 3, 3]
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+blesses	2.6	0.66332	[1, 3, 3, 3, 3, 3, 2, 3, 2, 3]
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+blessings	2.5	0.92195	[3, 3, 3, 2, 1, 3, 2, 3, 4, 1]
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+bliss	2.7	0.78102	[3, 3, 3, 2, 1, 2, 4, 3, 3, 3]
+blissful	2.9	0.83066	[4, 4, 2, 3, 3, 3, 1, 3, 3, 3]
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+block	-1.9	1.13578	[-3, -2, -1, -2, 0, 0, -3, -2, -3, -3]
+blockbuster	2.9	0.9434	[3, 4, 3, 2, 3, 4, 3, 2, 1, 4]
+blocked	-1.1	1.13578	[-1, 0, 0, -1, -2, -1, -1, -4, -1, 0]
+blocking	-1.6	0.91652	[-1, -1, -1, -1, -2, -2, -4, -1, -2, -1]
+blocks	-0.9	1.13578	[-1, 0, -1, -2, -2, -2, -1, -1, 2, -1]
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+bold	1.6	0.66332	[2, 2, 2, 2, 1, 2, 0, 2, 1, 2]
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+boldest	1.6	1.11355	[1, 3, 2, 3, 0, 0, 2, 3, 1, 1]
+boldface	0.3	0.64031	[1, 0, 0, 0, 0, 0, 0, 2, 0, 0]
+boldfaced	-0.1	1.22066	[0, 0, 0, 2, -1, -2, 2, -1, -1, 0]
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+boldly	1.5	1.62788	[3, -2, -1, 1, 2, 3, 2, 3, 2, 2]
+boldness	1.5	1.0247	[0, 1, 3, 1, 2, 0, 3, 1, 2, 2]
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+boost	1.7	0.64031	[1, 1, 2, 2, 2, 3, 1, 1, 2, 2]
+boosted	1.5	1.5	[-1, 1, 0, 2, 1, 2, 3, 3, 4, 0]
+boosting	1.4	0.91652	[1, 1, 3, 0, 2, 2, 0, 2, 1, 2]
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+bored	-1.1	0.9434	[-2, -1, -2, -1, 0, 0, -3, 0, -1, -1]
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+borer	-0.4	0.4899	[0, -1, 0, 0, -1, -1, 0, 0, 0, -1]
+borers	-1.2	0.9798	[-1, 0, -2, -1, -1, -3, -2, 0, -2, 0]
+bores	-1.3	0.78102	[-2, -1, -2, -1, -1, -1, -3, 0, -1, -1]
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+boring	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -1, -1, -2, -2]
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+botheration	-1.7	0.64031	[-1, -1, -1, -2, -2, -1, -2, -2, -2, -3]
+botherations	-1.3	0.64031	[-2, -2, -2, -1, -2, 0, -1, -1, -1, -1]
+bothered	-1.3	0.45826	[-1, -1, -2, -1, -2, -1, -1, -1, -1, -2]
+bothering	-1.6	0.4899	[-2, -1, -2, -2, -1, -1, -1, -2, -2, -2]
+bothers	-0.8	0.9798	[-1, -2, -1, -1, 2, -1, -1, -1, -1, -1]
+bothersome	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -2, -1, -1]
+boycott	-1.3	0.45826	[-2, -1, -1, -1, -1, -2, -1, -1, -2, -1]
+boycotted	-1.7	0.64031	[-1, -2, -2, -3, -1, -1, -2, -2, -2, -1]
+boycotting	-1.7	0.64031	[-2, -2, -2, 0, -2, -1, -2, -2, -2, -2]
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+braved	1.9	0.83066	[3, 1, 3, 1, 1, 2, 3, 2, 2, 1]
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+bravery	2.2	0.74833	[1, 2, 2, 2, 3, 2, 3, 3, 1, 3]
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+bravest	2.3	0.64031	[1, 3, 3, 2, 3, 2, 3, 2, 2, 2]
+breathtaking	2.0	1.26491	[3, 1, 3, 2, -1, 1, 2, 3, 3, 3]
+bribe	-0.8	1.98997	[-3, 0, -1, -2, -1, -2, -4, 1, 3, 1]
+bright	1.9	0.7	[2, 2, 1, 2, 1, 2, 1, 3, 3, 2]
+brighten	1.9	0.7	[2, 1, 1, 2, 3, 2, 1, 2, 2, 3]
+brightened	2.1	0.83066	[2, 3, 1, 1, 2, 2, 3, 1, 3, 3]
+brightener	1.0	1.18322	[0, 0, 0, 1, 0, 1, 2, 0, 3, 3]
+brighteners	1.0	0.89443	[0, 1, 0, 1, 1, 3, 0, 1, 2, 1]
+brightening	2.5	0.92195	[2, 3, 2, 1, 2, 3, 4, 4, 2, 2]
+brightens	1.5	0.5	[2, 1, 1, 2, 2, 1, 2, 2, 1, 1]
+brighter	1.6	0.66332	[1, 1, 1, 2, 2, 2, 1, 2, 1, 3]
+brightest	3.0	0.63246	[3, 3, 2, 3, 4, 3, 2, 3, 4, 3]
+brightly	1.5	0.67082	[2, 3, 1, 2, 1, 1, 2, 1, 1, 1]
+brightness	1.6	0.91652	[2, 2, 1, 1, 1, 3, 3, 0, 2, 1]
+brightnesses	1.4	0.91652	[2, 3, 1, 2, 1, 1, 0, 0, 2, 2]
+brights	0.4	0.66332	[0, 0, 2, 0, 0, 1, 0, 0, 1, 0]
+brightwork	1.1	0.83066	[1, 0, 1, 2, 1, 0, 3, 1, 1, 1]
+brilliance	2.9	0.83066	[4, 3, 2, 4, 4, 3, 2, 3, 2, 2]
+brilliances	2.9	0.83066	[3, 4, 3, 4, 4, 2, 3, 2, 2, 2]
+brilliancies	2.3	1.18743	[1, 4, 1, 3, 3, 2, 1, 3, 4, 1]
+brilliancy	2.6	1.0198	[4, 3, 2, 4, 2, 3, 1, 3, 1, 3]
+brilliant	2.8	0.6	[2, 3, 3, 2, 3, 3, 4, 2, 3, 3]
+brilliantine	0.8	1.16619	[-1, 3, 1, 0, 1, 0, 2, 0, 2, 0]
+brilliantines	2.0	1.34164	[0, 1, 4, 2, 3, 1, 3, 0, 3, 3]
+brilliantly	3.0	0.44721	[3, 2, 3, 3, 3, 3, 3, 3, 4, 3]
+brilliants	1.9	0.83066	[3, 1, 2, 1, 2, 1, 3, 2, 1, 3]
+brisk	0.6	0.8	[0, 0, 0, 0, 1, 1, 0, 2, 0, 2]
+broke	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -1, -2, -2]
+broken	-2.1	0.53852	[-2, -2, -2, -2, -3, -2, -1, -3, -2, -2]
+brooding	0.1	1.3	[3, 0, -1, -1, -1, 1, 1, -1, 1, -1]
+brutal	-3.1	0.7	[-3, -3, -4, -2, -3, -4, -3, -4, -3, -2]
+brutalise	-2.7	1.1	[-4, -3, -3, -4, -3, -2, -2, -3, 0, -3]
+brutalised	-2.9	0.83066	[-3, -3, -2, -3, -3, -4, -4, -1, -3, -3]
+brutalises	-3.2	0.4	[-3, -3, -3, -3, -3, -4, -4, -3, -3, -3]
+brutalising	-2.8	0.74833	[-3, -3, -4, -3, -2, -3, -3, -3, -1, -3]
+brutalities	-2.6	1.0198	[-4, -2, -2, -4, -2, -4, -2, -3, -1, -2]
+brutality	-3.0	0.63246	[-2, -3, -4, -2, -3, -3, -3, -4, -3, -3]
+brutalization	-2.1	2.16564	[-3, -2, -4, -2, -4, -4, 2, -3, 2, -3]
+brutalizations	-2.3	0.64031	[-2, -2, -3, -2, -1, -3, -3, -2, -2, -3]
+brutalize	-2.9	0.7	[-3, -4, -3, -3, -2, -2, -3, -4, -2, -3]
+brutalized	-2.4	0.4899	[-3, -2, -2, -3, -2, -2, -3, -3, -2, -2]
+brutalizes	-3.2	0.6	[-4, -4, -3, -2, -3, -4, -3, -3, -3, -3]
+brutalizing	-3.4	0.66332	[-4, -3, -4, -3, -4, -4, -3, -4, -2, -3]
+brutally	-3.0	0.44721	[-3, -3, -3, -3, -3, -3, -3, -2, -3, -4]
+bullied	-3.1	0.9434	[-4, -4, -4, -2, -2, -4, -4, -3, -2, -2]
+bullshit	-2.8	0.6	[-3, -3, -3, -3, -3, -4, -2, -3, -2, -2]
+bully	-2.2	1.6	[-2, -3, -3, -4, -2, -1, 2, -3, -3, -3]
+bullying	-2.9	0.7	[-3, -2, -3, -2, -4, -2, -3, -3, -4, -3]
+bummer	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -1, -2, -2, -1]
+buoyant	0.9	0.83066	[0, 1, 1, 2, 1, 0, 0, 2, 0, 2]
+burden	-1.9	0.53852	[-2, -2, -1, -2, -3, -2, -1, -2, -2, -2]
+burdened	-1.7	0.45826	[-2, -2, -2, -2, -1, -2, -1, -2, -2, -1]
+burdener	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -2, -1, -2, -1]
+burdeners	-1.7	1.00499	[-2, -2, -2, -1, -3, -2, 0, 0, -2, -3]
+burdening	-1.4	0.66332	[-2, -1, -2, -2, -1, -1, -1, 0, -2, -2]
+burdens	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -1, -2, -2]
+burdensome	-1.8	0.9798	[-1, -1, -3, -2, -1, -2, -2, -1, -4, -1]
+bwahaha	0.4	1.0198	[0, 1, 0, 1, 0, 2, -1, -1, 2, 0]
+bwahahah	2.5	0.92195	[3, 4, 2, 2, 2, 3, 1, 2, 2, 4]
+calm	1.3	0.78102	[1, 1, 0, 1, 2, 3, 2, 1, 1, 1]
+calmative	1.1	0.9434	[3, 2, -1, 1, 1, 1, 1, 1, 1, 1]
+calmatives	0.5	0.80623	[-1, 1, 0, 1, 0, 0, 1, 2, 0, 1]
+calmed	1.6	0.4899	[2, 2, 2, 1, 1, 1, 2, 1, 2, 2]
+calmer	1.5	0.67082	[1, 2, 3, 1, 1, 1, 2, 1, 2, 1]
+calmest	1.6	0.8	[3, 2, 2, 2, 1, 1, 0, 2, 1, 2]
+calming	1.7	0.78102	[2, 1, 3, 2, 2, 1, 3, 1, 1, 1]
+calmly	1.3	0.9	[0, 0, 1, 3, 2, 2, 1, 1, 2, 1]
+calmness	1.7	0.9	[1, 1, 1, 2, 2, 2, 1, 4, 1, 2]
+calmnesses	1.6	0.4899	[1, 2, 1, 2, 1, 2, 2, 2, 1, 2]
+calmodulin	0.2	0.4	[0, 0, 0, 0, 0, 0, 1, 0, 0, 1]
+calms	1.3	0.64031	[2, 1, 1, 2, 0, 1, 1, 2, 2, 1]
+can't stand	-2.0	0.63246	[-2, -2, -2, -1, -1, -2, -3, -2, -2, -3]
+cancel	-1.0	0.63246	[-2, -1, -1, -1, -1, 0, -1, 0, -2, -1]
+cancelled	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -2, -1, -1]
+cancelling	-0.8	0.74833	[0, 0, -1, 0, -1, -1, 0, -2, -1, -2]
+cancels	-0.9	0.53852	[0, -1, 0, -1, -1, -1, -1, -1, -2, -1]
+cancer	-3.4	0.8	[-2, -4, -3, -4, -4, -2, -3, -4, -4, -4]
+capable	1.6	0.4899	[1, 2, 2, 2, 1, 1, 2, 2, 1, 2]
+captivated	1.6	0.4899	[2, 1, 2, 2, 2, 2, 1, 2, 1, 1]
+care	2.2	0.74833	[2, 1, 2, 1, 2, 2, 3, 3, 3, 3]
+cared	1.8	0.74833	[1, 2, 1, 3, 1, 2, 2, 2, 3, 1]
+carefree	1.7	0.64031	[1, 1, 2, 2, 2, 2, 1, 1, 2, 3]
+careful	0.6	1.11355	[3, 0, 0, 0, 1, 0, -1, 2, 1, 0]
+carefully	0.5	0.67082	[1, 0, 1, 1, 0, 1, 0, 1, 1, -1]
+carefulness	2.0	0.44721	[3, 2, 2, 1, 2, 2, 2, 2, 2, 2]
+careless	-1.5	0.5	[-2, -1, -1, -2, -2, -1, -2, -2, -1, -1]
+carelessly	-1.0	0.44721	[-1, -1, -1, -2, -1, 0, -1, -1, -1, -1]
+carelessness	-1.4	0.4899	[-2, -1, -1, -2, -1, -2, -1, -1, -2, -1]
+carelessnesses	-1.6	1.11355	[-4, -2, -2, -3, -1, 0, -1, -1, -1, -1]
+cares	2.0	0.7746	[2, 3, 1, 3, 1, 2, 2, 2, 3, 1]
+caring	2.2	0.4	[2, 3, 2, 2, 2, 2, 2, 3, 2, 2]
+casual	0.8	0.74833	[1, 1, 0, 1, 0, 2, 0, 1, 2, 0]
+casually	0.7	1.00499	[1, 0, 0, 0, 1, 0, 0, 3, 2, 0]
+casualty	-2.4	0.91652	[-4, -3, -3, -2, -1, -2, -3, -1, -2, -3]
+catastrophe	-3.4	0.4899	[-3, -3, -3, -4, -4, -3, -3, -3, -4, -4]
+catastrophic	-2.2	2.22711	[-3, -2, -4, -4, -4, -3, -2, -4, 2, 2]
+cautious	-0.4	0.66332	[0, 1, -1, 0, 0, 0, -1, -1, -1, -1]
+celebrate	2.7	1.00499	[4, 4, 3, 2, 4, 2, 2, 2, 3, 1]
+celebrated	2.7	0.78102	[2, 3, 3, 2, 3, 4, 3, 3, 1, 3]
+celebrates	2.7	0.64031	[2, 3, 3, 2, 2, 3, 3, 3, 4, 2]
+celebrating	2.7	0.64031	[3, 3, 4, 2, 2, 2, 3, 3, 2, 3]
+censor	-2.0	1.34164	[0, -3, -2, -3, -3, 0, -4, -1, -1, -3]
+censored	-0.6	1.68523	[-1, -1, -1, 2, -3, -2, -1, -1, -1, 3]
+censors	-1.2	1.07703	[-1, 0, -3, 0, -1, 0, -1, -2, -1, -3]
+certain	1.1	0.7	[1, 0, 2, 0, 2, 2, 1, 1, 1, 1]
+certainly	1.4	1.0198	[3, 2, 0, 1, 3, 1, 0, 1, 1, 2]
+certainties	0.9	1.44568	[0, -2, 4, 0, 1, 1, 1, 1, 2, 1]
+certainty	1.0	0.89443	[2, 1, 0, 1, 0, 0, 2, 2, 2, 0]
+chagrin	-1.9	0.53852	[-1, -2, -3, -2, -1, -2, -2, -2, -2, -2]
+chagrined	-1.4	1.2	[-1, -2, 2, -1, -2, -2, -2, -2, -2, -2]
+challenge	0.3	1.00499	[1, 0, -1, 1, 1, -1, 1, 0, 2, -1]
+challenged	-0.4	1.62481	[0, -2, 1, -1, -3, -1, 3, -1, 1, -1]
+challenger	0.5	1.43178	[0, 0, 2, -1, -2, 1, 3, 0, 2, 0]
+challengers	0.4	1.56205	[0, -2, -1, 1, 1, 2, 3, 2, -1, -1]
+challenges	0.3	1.48661	[0, -1, 2, -1, -2, 0, 3, 0, 2, 0]
+challenging	0.6	0.91652	[0, 0, 0, 1, 1, -1, 0, 2, 2, 1]
+challengingly	-0.6	1.68523	[0, -1, -2, 1, -3, 2, -2, -1, 2, -2]
+champ	2.1	0.83066	[2, 2, 2, 3, 2, 3, 2, 0, 3, 2]
+champac	-0.2	0.6	[0, 0, -2, 0, 0, 0, 0, 0, 0, 0]
+champagne	1.2	1.07703	[1, 2, 2, 3, 0, 2, 0, 0, 2, 0]
+champagnes	0.5	0.92195	[0, 0, 0, 0, 0, 1, 1, 3, 0, 0]
+champaign	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
+champaigns	0.5	0.67082	[1, 0, 0, 0, 0, 0, 0, 1, 2, 1]
+champaks	-0.2	0.6	[0, 0, 0, 0, 0, 0, -2, 0, 0, 0]
+champed	1.0	0.63246	[1, 1, 2, 1, 1, 2, 1, 0, 0, 1]
+champer	-0.1	0.53852	[0, -1, 1, 0, 0, 0, 0, -1, 0, 0]
+champers	0.5	0.67082	[1, 0, 0, 0, 0, 0, 0, 1, 1, 2]
+champerties	-0.1	0.83066	[0, -1, 1, 1, 0, 0, 0, 0, -2, 0]
+champertous	0.3	0.78102	[0, 0, 0, 1, -1, 2, 1, 0, 0, 0]
+champerty	-0.2	1.32665	[-2, -1, 0, -1, 0, 0, 0, -2, 2, 2]
+champignon	0.4	0.8	[0, 0, 0, 0, 0, 2, 0, 2, 0, 0]
+champignons	0.2	0.6	[0, 2, 0, 0, 0, 0, 0, 0, 0, 0]
+champing	0.7	1.34536	[0, 2, 0, 3, 1, 1, 2, 0, -2, 0]
+champion	2.9	0.83066	[3, 2, 3, 4, 4, 3, 2, 2, 4, 2]
+championed	1.2	1.53623	[2, 1, 3, 1, 1, -3, 2, 2, 1, 2]
+championing	1.8	0.9798	[1, 3, 2, 0, 3, 1, 2, 2, 1, 3]
+champions	2.4	1.42829	[4, 0, 0, 3, 1, 3, 4, 3, 3, 3]
+championship	1.9	1.04403	[3, 1, 1, 3, 2, 1, 3, 3, 0, 2]
+championships	2.2	0.74833	[2, 2, 1, 2, 3, 2, 4, 2, 2, 2]
+champs	1.8	0.4	[2, 2, 2, 2, 1, 2, 1, 2, 2, 2]
+champy	1.0	1.0	[3, 0, 0, 0, 0, 2, 1, 2, 1, 1]
+chance	1.0	0.7746	[1, 1, 0, 0, 0, 2, 1, 2, 1, 2]
+chances	0.8	0.4	[0, 1, 1, 0, 1, 1, 1, 1, 1, 1]
+chaos	-2.7	0.9	[-2, -2, -3, -1, -4, -3, -3, -2, -3, -4]
+chaotic	-2.2	1.4	[-3, -2, -1, -2, -3, 1, -2, -2, -4, -4]
+charged	-0.8	0.87178	[-1, -2, -2, -1, -1, 0, -1, 1, 0, -1]
+charges	-1.1	0.7	[-2, -2, -2, -1, -1, 0, -1, -1, 0, -1]
+charitable	1.7	0.64031	[1, 2, 1, 2, 2, 1, 2, 1, 3, 2]
+charitableness	1.9	0.9434	[3, 1, 1, 3, 1, 3, 3, 2, 1, 1]
+charitablenesses	1.6	1.74356	[2, 2, 3, 4, 1, -1, -2, 3, 2, 2]
+charitably	1.4	0.66332	[1, 2, 1, 2, 2, 1, 0, 1, 2, 2]
+charities	2.2	0.6	[3, 3, 2, 2, 1, 2, 2, 3, 2, 2]
+charity	1.8	0.87178	[1, 3, 2, 2, 2, 1, 2, 0, 2, 3]
+charm	1.7	0.78102	[3, 1, 1, 3, 2, 2, 1, 1, 1, 2]
+charmed	2.0	0.63246	[3, 1, 2, 2, 2, 3, 1, 2, 2, 2]
+charmer	1.9	0.53852	[3, 2, 2, 2, 2, 2, 1, 1, 2, 2]
+charmers	2.1	0.83066	[2, 1, 2, 2, 4, 3, 2, 1, 2, 2]
+charmeuse	0.3	0.78102	[0, 0, 0, 1, 0, 2, 1, 0, -1, 0]
+charmeuses	0.4	0.66332	[0, 0, 1, 0, 1, 0, 0, 0, 0, 2]
+charming	2.8	0.4	[3, 3, 3, 3, 3, 3, 2, 3, 2, 3]
+charminger	1.5	0.67082	[2, 3, 1, 2, 1, 1, 2, 1, 1, 1]
+charmingest	2.4	0.66332	[2, 3, 3, 1, 3, 2, 3, 3, 2, 2]
+charmingly	2.2	0.87178	[2, 2, 2, 1, 2, 2, 3, 3, 4, 1]
+charmless	-1.8	0.87178	[-3, -1, -3, -1, -1, -1, -2, -1, -3, -2]
+charms	1.9	0.7	[1, 2, 3, 2, 1, 2, 3, 1, 2, 2]
+chastise	-2.5	0.92195	[-4, -3, -2, -1, -4, -3, -2, -2, -2, -2]
+chastised	-2.2	1.16619	[-2, -3, -2, -4, -1, -1, -3, 0, -3, -3]
+chastises	-1.7	1.61555	[-3, -3, -3, -1, 1, -2, 1, -1, -2, -4]
+chastising	-1.7	0.78102	[-2, -3, -2, -2, -2, 0, -1, -1, -2, -2]
+cheat	-2.0	0.7746	[-2, -3, -3, -2, -2, -1, -1, -1, -2, -3]
+cheated	-2.3	0.64031	[-2, -4, -2, -2, -2, -2, -3, -2, -2, -2]
+cheater	-2.5	0.67082	[-2, -4, -2, -3, -2, -2, -3, -2, -3, -2]
+cheaters	-1.9	0.83066	[-2, -2, -2, -1, -1, -4, -2, -1, -2, -2]
+cheating	-2.6	0.91652	[-2, -3, -3, -2, -4, -4, -3, -2, -1, -2]
+cheats	-1.8	0.6	[-3, -1, -2, -1, -2, -1, -2, -2, -2, -2]
+cheer	2.3	0.64031	[2, 1, 2, 2, 2, 3, 3, 3, 2, 3]
+cheered	2.3	0.78102	[2, 3, 3, 4, 2, 1, 2, 2, 2, 2]
+cheerer	1.7	0.45826	[1, 2, 2, 2, 1, 1, 2, 2, 2, 2]
+cheerers	1.8	0.87178	[2, 2, 3, 2, 1, 2, 0, 1, 3, 2]
+cheerful	2.5	0.67082	[3, 2, 3, 2, 2, 2, 4, 2, 3, 2]
+cheerfuller	1.9	0.83066	[3, 3, 2, 3, 2, 1, 1, 2, 1, 1]
+cheerfullest	3.2	0.87178	[4, 4, 4, 4, 3, 2, 2, 3, 2, 4]
+cheerfully	2.1	0.83066	[3, 2, 2, 2, 1, 3, 1, 3, 1, 3]
+cheerfulness	2.1	0.9434	[3, 2, 1, 2, 3, 4, 1, 2, 1, 2]
+cheerier	2.6	0.4899	[2, 2, 3, 3, 2, 3, 3, 2, 3, 3]
+cheeriest	2.2	0.6	[3, 2, 3, 1, 2, 2, 3, 2, 2, 2]
+cheerily	2.5	0.67082	[3, 3, 2, 3, 2, 4, 2, 2, 2, 2]
+cheeriness	2.5	0.67082	[3, 2, 4, 2, 3, 2, 3, 2, 2, 2]
+cheering	2.3	0.64031	[3, 3, 2, 1, 3, 2, 2, 2, 3, 2]
+cheerio	1.2	0.6	[2, 1, 1, 1, 2, 1, 1, 1, 2, 0]
+cheerlead	1.7	0.78102	[1, 2, 0, 2, 2, 2, 2, 3, 1, 2]
+cheerleader	0.9	0.9434	[1, 1, 0, 2, 1, 0, 0, 1, 0, 3]
+cheerleaders	1.2	1.07703	[2, 0, 0, 1, 1, 0, 3, 3, 1, 1]
+cheerleading	1.2	1.07703	[2, 2, 0, 0, 1, 0, 3, 2, 0, 2]
+cheerleads	1.2	1.07703	[2, 3, 0, 3, 1, 0, 0, 1, 1, 1]
+cheerled	1.5	1.11803	[0, 2, 1, 4, 2, 2, 2, 1, 1, 0]
+cheerless	-1.7	1.1	[-2, -3, -2, -2, -3, -2, -1, -1, 1, -2]
+cheerlessly	-0.8	1.98997	[-2, 4, -1, -2, -1, -2, -2, -2, 2, -2]
+cheerlessness	-1.7	1.48661	[-2, -1, -2, -3, -2, -4, -1, 2, -2, -2]
+cheerly	2.4	0.66332	[2, 2, 3, 2, 2, 3, 4, 2, 2, 2]
+cheers	2.1	1.3	[2, 2, 1, 3, 2, 3, 3, 4, -1, 2]
+cheery	2.6	0.66332	[3, 2, 2, 3, 2, 3, 4, 2, 3, 2]
+cherish	1.6	1.49666	[0, 3, 3, 3, 2, 2, 2, 1, -2, 2]
+cherishable	2.0	1.41421	[-2, 2, 2, 2, 3, 2, 3, 3, 2, 3]
+cherished	2.3	0.64031	[3, 2, 2, 3, 2, 2, 1, 3, 2, 3]
+cherisher	2.2	0.4	[2, 2, 3, 2, 2, 2, 2, 3, 2, 2]
+cherishers	1.9	0.7	[3, 3, 2, 2, 1, 1, 2, 2, 2, 1]
+cherishes	2.2	0.74833	[2, 2, 3, 2, 2, 2, 2, 4, 2, 1]
+cherishing	2.0	0.7746	[3, 3, 2, 2, 1, 2, 1, 3, 2, 1]
+chic	1.1	1.3	[1, 2, 2, -2, 2, 0, 1, 1, 3, 1]
+childish	-1.2	0.74833	[-1, -1, -2, -3, -1, 0, -1, -1, -1, -1]
+chilling	-0.1	1.92094	[3, -2, 0, 1, -2, -2, -1, -2, 1, 3]
+choke	-2.5	0.92195	[-1, -2, -3, -3, -2, -4, -2, -4, -2, -2]
+choked	-2.1	1.3	[-4, -3, 0, -2, -1, -3, -3, -2, 0, -3]
+chokes	-2.0	0.89443	[-4, -3, -1, -2, -1, -2, -2, -2, -1, -2]
+choking	-2.0	1.26491	[-4, -2, -2, -3, -2, -2, -3, -1, 1, -2]
+chuckle	1.7	0.45826	[2, 1, 2, 2, 2, 2, 1, 1, 2, 2]
+chuckled	1.2	0.9798	[2, 2, 1, 1, 2, 0, 1, 2, -1, 2]
+chucklehead	-1.9	0.53852	[-2, -2, -1, -3, -2, -2, -2, -2, -1, -2]
+chuckleheaded	-1.3	1.84662	[-3, -4, -2, 0, 3, -1, -2, 0, -2, -2]
+chuckleheads	-1.1	0.9434	[-1, -2, 0, -1, -1, -3, 0, 0, -2, -1]
+chuckler	0.8	1.07703	[2, 1, -1, 0, 2, 1, 1, 2, -1, 1]
+chucklers	1.2	0.87178	[1, 1, 2, 3, 1, 0, 1, 0, 2, 1]
+chuckles	1.1	1.13578	[2, 2, -1, 1, 2, 1, 1, 2, -1, 2]
+chucklesome	1.1	0.53852	[1, 1, 2, 1, 1, 1, 0, 2, 1, 1]
+chuckling	1.4	0.4899	[1, 2, 1, 2, 1, 1, 2, 2, 1, 1]
+chucklingly	1.2	0.4	[1, 1, 1, 1, 2, 1, 1, 1, 2, 1]
+clarifies	0.9	1.13578	[-2, 1, 0, 2, 1, 2, 2, 1, 1, 1]
+clarity	1.7	0.78102	[2, 1, 2, 3, 3, 1, 1, 2, 1, 1]
+classy	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
+clean	1.7	0.78102	[3, 1, 2, 1, 2, 1, 3, 2, 1, 1]
+cleaner	0.7	0.78102	[1, 0, 1, 0, 0, 0, 2, 1, 2, 0]
+clear	1.6	1.2	[2, 1, 1, 0, 3, 1, 2, 4, 2, 0]
+cleared	0.4	0.4899	[0, 0, 1, 1, 0, 0, 0, 0, 1, 1]
+clearly	1.7	0.78102	[2, 2, 2, 2, 1, 2, 0, 2, 1, 3]
+clears	0.3	0.78102	[0, 1, 0, 0, 0, -1, 1, 2, 0, 0]
+clever	2.0	0.7746	[2, 1, 2, 2, 2, 1, 3, 1, 3, 3]
+cleverer	2.0	0.44721	[2, 2, 2, 3, 2, 2, 1, 2, 2, 2]
+cleverest	2.6	0.91652	[4, 3, 2, 2, 4, 3, 2, 1, 2, 3]
+cleverish	1.0	1.18322	[1, 1, 1, 1, 1, 1, 2, 1, -2, 3]
+cleverly	2.3	0.45826	[2, 3, 2, 2, 2, 3, 2, 2, 3, 2]
+cleverness	2.3	0.9	[2, 4, 2, 2, 1, 3, 3, 3, 1, 2]
+clevernesses	1.4	0.66332	[1, 1, 1, 2, 2, 2, 2, 0, 2, 1]
+clouded	-0.2	0.9798	[-2, 0, 2, 0, 0, -1, 0, -1, 0, 0]
+clueless	-1.5	0.5	[-1, -2, -1, -2, -2, -1, -1, -1, -2, -2]
+cock	-0.6	1.49666	[0, 0, -4, 0, 0, 1, 0, -3, 0, 0]
+cocksucker	-3.1	0.83066	[-3, -4, -2, -2, -4, -4, -4, -2, -3, -3]
+cocksuckers	-2.6	1.42829	[-4, -3, -4, -3, -3, 1, -3, -1, -3, -3]
+cocky	-0.5	1.0247	[2, 0, -1, 0, -1, -2, 0, -1, -1, -1]
+coerced	-1.5	0.67082	[-1, -2, -2, -2, -1, 0, -1, -2, -2, -2]
+collapse	-2.2	0.87178	[-3, -1, -2, -4, -3, -2, -2, -2, -1, -2]
+collapsed	-1.1	1.64012	[-1, -2, -2, -1, -2, -2, 2, 2, -3, -2]
+collapses	-1.2	0.87178	[-2, -1, -2, 0, -2, 0, 0, -2, -1, -2]
+collapsing	-1.2	0.6	[-1, -1, -2, -2, -2, -1, 0, -1, -1, -1]
+collide	-0.3	1.61555	[-3, 0, -1, 3, 0, -1, -1, 2, -1, -1]
+collides	-1.1	1.22066	[-2, -2, -1, -1, 0, -2, 2, -2, -1, -2]
+colliding	-0.5	1.36015	[-2, 2, -1, -1, 0, -1, -2, 2, -1, -1]
+collision	-1.5	0.67082	[-1, -1, -2, -1, -2, -1, -1, -3, -2, -1]
+collisions	-1.1	0.7	[0, -2, -1, 0, -1, -1, -2, -2, -1, -1]
+colluding	-1.2	1.32665	[-1, -1, -2, -2, 0, -3, 2, -2, -1, -2]
+combat	-1.4	1.0198	[0, -2, 0, -2, -2, -2, -1, -3, 0, -2]
+combats	-0.8	1.16619	[0, -2, -3, -1, 0, 0, 0, -1, 1, -2]
+comedian	1.6	1.0198	[1, 0, 2, 3, 2, 0, 3, 1, 2, 2]
+comedians	1.2	1.16619	[0, 0, 0, 2, 3, 1, 3, 2, 0, 1]
+comedic	1.7	0.64031	[2, 1, 1, 3, 1, 2, 2, 2, 1, 2]
+comedically	2.1	0.7	[3, 2, 2, 1, 2, 3, 3, 2, 1, 2]
+comedienne	0.6	0.66332	[0, 2, 1, 0, 1, 1, 0, 1, 0, 0]
+comediennes	1.6	1.11355	[2, 1, 3, 0, 0, 3, 1, 1, 2, 3]
+comedies	1.7	1.00499	[0, 2, 1, 3, 3, 3, 1, 1, 2, 1]
+comedo	0.3	0.9	[0, 0, 0, 0, -1, 0, 2, 0, 2, 0]
+comedones	-0.8	0.9798	[0, 0, 0, -1, 0, -3, 0, -1, -1, -2]
+comedown	-0.8	1.07703	[-1, -1, -1, 0, -2, -1, 2, -1, -2, -1]
+comedowns	-0.9	0.53852	[-1, -1, -1, -1, 0, -2, 0, -1, -1, -1]
+comedy	1.5	0.67082	[1, 1, 2, 1, 3, 2, 1, 1, 2, 1]
+comfort	1.5	0.67082	[1, 3, 1, 2, 1, 1, 2, 1, 1, 2]
+comfortable	2.3	0.64031	[1, 2, 3, 2, 2, 3, 3, 3, 2, 2]
+comfortableness	1.3	1.48661	[4, 2, 2, 3, 1, 1, 1, -1, -1, 1]
+comfortably	1.8	0.74833	[1, 2, 2, 1, 3, 3, 1, 2, 1, 2]
+comforted	1.8	0.6	[2, 2, 2, 0, 2, 2, 2, 2, 2, 2]
+comforter	1.9	0.53852	[2, 3, 2, 2, 2, 1, 2, 2, 2, 1]
+comforters	1.2	0.6	[2, 1, 0, 2, 1, 1, 2, 1, 1, 1]
+comforting	1.7	0.64031	[1, 2, 1, 1, 2, 2, 2, 3, 2, 1]
+comfortingly	1.7	0.45826	[1, 2, 1, 2, 2, 1, 2, 2, 2, 2]
+comfortless	-1.8	0.6	[-3, -2, -1, -2, -1, -2, -1, -2, -2, -2]
+comforts	2.1	0.7	[3, 1, 3, 1, 2, 2, 3, 2, 2, 2]
+commend	1.9	0.7	[1, 2, 2, 1, 2, 1, 2, 3, 2, 3]
+commended	1.9	0.9434	[1, 3, 2, 3, 2, 2, 0, 1, 3, 2]
+commit	1.2	0.87178	[1, 0, 2, 2, 0, 0, 2, 2, 1, 2]
+commitment	1.6	0.91652	[3, 1, 2, 0, 3, 1, 2, 1, 2, 1]
+commitments	0.5	0.92195	[1, 3, 0, 0, 0, 0, 0, 0, 0, 1]
+commits	0.1	1.13578	[0, -1, 0, 2, 1, -1, 1, 1, -2, 0]
+committed	1.1	0.7	[0, 1, 1, 2, 0, 2, 1, 1, 2, 1]
+committing	0.3	1.18743	[0, 1, 0, 3, 0, -2, 1, 0, 0, 0]
+compassion	2.0	0.7746	[3, 2, 1, 1, 2, 1, 3, 2, 2, 3]
+compassionate	2.2	0.87178	[0, 3, 3, 2, 2, 3, 3, 2, 2, 2]
+compassionated	1.6	0.66332	[3, 1, 2, 2, 1, 2, 2, 1, 1, 1]
+compassionately	1.7	1.41774	[1, 3, 3, 2, 1, 2, 3, 2, -2, 2]
+compassionateness	0.9	1.37477	[-3, 2, 2, 1, 1, 1, 2, 1, 1, 1]
+compassionates	1.6	0.4899	[2, 1, 2, 2, 1, 2, 2, 1, 1, 2]
+compassionating	1.6	0.91652	[3, 0, 2, 1, 3, 1, 2, 1, 2, 1]
+compassionless	-2.6	0.8	[-3, -2, -2, -3, -4, -3, -1, -2, -3, -3]
+compelled	0.2	1.07703	[-1, 0, 0, 0, 1, 2, -1, -1, 2, 0]
+compelling	0.9	0.94339	[1, 1, 1, 0, 1, 2, 2, -1, 2, 0]
+competent	1.3	0.78102	[1, 3, 1, 1, 2, 1, 1, 0, 2, 1]
+competitive	0.7	0.9	[0, 2, 0, 2, 0, 1, 0, 0, 0, 2]
+complacent	-0.3	1.1	[2, -1, -1, 1, -1, -1, -1, 1, -1, -1]
+complain	-1.5	0.67082	[-1, -1, -1, -2, -1, -2, -3, -2, -1, -1]
+complainant	-0.7	0.78102	[0, 0, -1, 0, 0, -2, 0, -1, -2, -1]
+complainants	-1.1	1.3	[-2, -1, 0, -2, -3, -2, -1, 1, -2, 1]
+complained	-1.7	0.64031	[-1, -3, -2, -2, -1, -1, -2, -2, -1, -2]
+complainer	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -2, -1, -2]
+complainers	-1.3	1.00499	[-2, -1, -1, -2, -3, 1, -1, -1, -2, -1]
+complaining	-0.8	1.249	[-2, -1, -1, -1, -2, -1, -1, 2, 1, -2]
+complainingly	-1.7	0.64031	[-1, -2, -1, -2, -1, -2, -1, -2, -3, -2]
+complains	-1.6	0.66332	[-1, -2, -1, -2, -2, -3, -1, -1, -1, -2]
+complaint	-1.2	1.249	[-1, -1, -2, -2, -1, -3, -1, -1, 2, -2]
+complaints	-1.7	0.45826	[-2, -2, -2, -1, -2, -2, -2, -1, -1, -2]
+compliment	2.1	0.7	[2, 2, 3, 1, 2, 3, 3, 1, 2, 2]
+complimentarily	1.7	0.45826	[2, 2, 2, 2, 1, 1, 2, 1, 2, 2]
+complimentary	1.9	0.7	[1, 2, 2, 1, 2, 1, 2, 3, 3, 2]
+complimented	1.8	1.4	[3, 2, 2, 2, 3, 2, -2, 3, 1, 2]
+complimenting	2.3	0.64031	[2, 2, 1, 3, 3, 2, 2, 3, 3, 2]
+compliments	1.7	0.45826	[2, 1, 2, 2, 1, 2, 2, 1, 2, 2]
+comprehensive	1.0	0.63246	[1, 1, 1, 0, 2, 2, 1, 0, 1, 1]
+conciliate	1.0	1.18322	[2, 1, 1, 0, 2, 2, -2, 2, 1, 1]
+conciliated	1.1	0.9434	[1, 3, 0, 0, 2, 0, 2, 1, 1, 1]
+conciliates	1.1	0.9434	[1, 3, 0, 0, 2, 0, 2, 1, 1, 1]
+conciliating	1.3	0.78102	[2, 2, 1, 1, 2, 0, 2, 1, 2, 0]
+condemn	-1.6	1.0198	[-2, -2, -1, -2, -2, 1, -2, -3, -1, -2]
+condemnation	-2.8	0.9798	[-3, -4, -2, -4, -2, -4, -2, -1, -3, -3]
+condemned	-1.9	1.81384	[2, -2, -2, -3, -2, -3, -3, -4, 1, -3]
+condemns	-2.3	0.64031	[-2, -2, -3, -3, -3, -2, -2, -3, -1, -2]
+confidence	2.3	0.64031	[3, 3, 3, 3, 1, 2, 2, 2, 2, 2]
+confident	2.2	0.87178	[1, 3, 3, 2, 3, 1, 3, 2, 1, 3]
+confidently	2.1	0.53852	[2, 2, 3, 1, 2, 2, 2, 2, 3, 2]
+conflict	-1.3	0.45826	[-2, -2, -1, -2, -1, -1, -1, -1, -1, -1]
+conflicting	-1.7	0.64031	[-1, -2, -3, -1, -2, -1, -2, -1, -2, -2]
+conflictive	-1.8	0.6	[-2, -2, -2, -2, -1, -1, -3, -2, -1, -2]
+conflicts	-1.6	0.8	[-1, -1, -1, -2, -1, -1, -3, -2, -1, -3]
+confront	-0.7	0.78102	[0, -1, -1, 0, 1, -1, -1, -2, -1, -1]
+confrontation	-1.3	1.55242	[-3, -2, -3, -2, -1, -2, 1, 2, -1, -2]
+confrontational	-1.6	0.66332	[-1, -2, -1, -2, -1, -2, -1, -2, -3, -1]
+confrontationist	-1.0	1.34164	[-1, -2, -2, 2, 1, -1, -2, -1, -2, -2]
+confrontationists	-1.2	1.46969	[-2, -3, -1, -2, 2, 1, -1, -2, -2, -2]
+confrontations	-1.5	1.0247	[-1, -3, -2, -1, -3, 0, -2, -2, 0, -1]
+confronted	-0.8	0.74833	[-1, -2, -1, -1, -1, -1, -1, -1, 1, 0]
+confronter	-0.3	1.1	[0, -2, 1, -2, 0, -1, -1, 0, 1, 1]
+confronters	-1.3	1.26886	[-3, -2, -2, -2, -1, -2, 1, 1, -1, -2]
+confronting	-0.6	1.11355	[-2, -1, -1, 0, -2, 2, -1, 0, 0, -1]
+confronts	-0.9	0.53852	[-1, -1, -1, -1, 0, -1, 0, -1, -2, -1]
+confuse	-0.9	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, 0, -1]
+confused	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -2]
+confusedly	-0.6	1.42829	[-3, -1, -1, 1, -1, -1, -2, 2, 1, -1]
+confusedness	-1.5	0.67082	[-3, -1, -1, -2, -1, -2, -2, -1, -1, -1]
+confuses	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -2]
+confusing	-0.9	0.7	[-1, -1, -1, -2, -1, -1, 1, -1, -1, -1]
+confusingly	-1.4	0.66332	[-1, -1, -1, -1, -3, -1, -2, -1, -1, -2]
+confusion	-1.2	0.6	[-1, -1, -1, -1, -1, -2, 0, -1, -2, -2]
+confusional	-1.2	0.6	[-2, -2, 0, -1, -2, -1, -1, -1, -1, -1]
+confusions	-0.9	1.04403	[-1, -2, -1, -1, -1, 2, -2, -1, -1, -1]
+congrats	2.4	0.91652	[1, 3, 3, 3, 2, 2, 4, 1, 2, 3]
+congratulate	2.2	1.249	[3, 3, 2, 3, -1, 2, 1, 3, 3, 3]
+congratulation	2.9	0.9434	[3, 3, 3, 2, 4, 2, 4, 3, 4, 1]
+congratulations	2.9	0.53852	[2, 3, 3, 3, 3, 3, 3, 3, 4, 2]
+consent	0.9	0.7	[0, 0, 1, 1, 1, 2, 1, 2, 0, 1]
+consents	1.0	0.63246	[0, 2, 1, 0, 1, 1, 1, 2, 1, 1]
+considerate	1.9	1.22066	[2, -1, 3, 2, 2, 2, 4, 1, 2, 2]
+consolable	1.1	0.53852	[1, 1, 2, 1, 0, 1, 1, 1, 2, 1]
+conspiracy	-2.4	0.66332	[-2, -2, -3, -3, -2, -2, -4, -2, -2, -2]
+constrained	-0.4	1.0198	[-1, 0, -1, -1, -1, -1, 2, -1, 1, -1]
+contagion	-2.0	1.18322	[-1, 0, -2, -1, -2, -4, -2, -4, -2, -2]
+contagions	-1.5	0.92195	[-2, -2, -2, -2, 1, -2, -1, -1, -2, -2]
+contagious	-1.4	0.91652	[-2, -2, -2, 0, -1, -1, -2, 0, -1, -3]
+contempt	-2.8	0.6	[-3, -3, -4, -2, -3, -2, -3, -3, -2, -3]
+contemptibilities	-2.0	1.09545	[-2, 1, -2, -2, -3, -3, -3, -2, -2, -2]
+contemptibility	-0.9	1.51327	[-2, -1, -3, -1, 0, -3, -1, 1, 2, -1]
+contemptible	-1.6	1.68523	[-2, -2, -3, -3, -2, -3, -1, -3, 1, 2]
+contemptibleness	-1.9	0.7	[-2, -2, -1, -2, -2, -1, -1, -2, -3, -3]
+contemptibly	-1.4	1.49666	[-3, 0, -2, -3, -2, -2, -1, -3, 1, 1]
+contempts	-1.0	1.48324	[-2, -2, -1, 0, 1, -1, -2, -3, 2, -2]
+contemptuous	-2.2	1.83303	[-2, -3, -4, -2, -3, -3, 3, -2, -3, -3]
+contemptuously	-2.4	0.8	[-1, -3, -2, -3, -3, -2, -1, -3, -3, -3]
+contemptuousness	-1.1	1.57797	[-3, -1, -2, 3, -2, 0, -1, -1, -2, -2]
+contend	0.2	1.07703	[0, 0, 1, 1, -2, 1, -1, 0, 2, 0]
+contender	0.5	1.0247	[1, 3, -1, 0, 0, 1, 0, 1, 0, 0]
+contented	1.4	1.56205	[1, 1, 3, 2, 2, 2, -3, 2, 2, 2]
+contentedly	1.9	0.9434	[3, 1, 2, 3, 2, 3, 0, 2, 1, 2]
+contentedness	1.4	0.4899	[1, 2, 1, 1, 2, 2, 2, 1, 1, 1]
+contentious	-1.2	1.4	[-2, -2, -2, -2, -2, -2, -1, 2, 1, -2]
+contentment	1.5	1.74642	[2, 1, 3, 2, 2, 1, 2, 4, 1, -3]
+contestable	0.6	1.0198	[2, -1, 1, 0, 1, -1, 1, 1, 2, 0]
+contradict	-1.3	0.78102	[-2, -1, -1, 0, -2, 0, -1, -2, -2, -2]
+contradictable	-1.0	0.63246	[-1, -1, -2, 0, -1, -1, 0, -1, -1, -2]
+contradicted	-1.3	0.45826	[-1, -1, -1, -1, -2, -1, -2, -1, -1, -2]
+contradicting	-1.3	0.9	[-2, -2, -2, -1, -2, -1, 1, -1, -1, -2]
+contradiction	-1.0	0.89443	[-1, 0, 0, -1, 0, -3, -2, -1, -1, -1]
+contradictions	-1.3	0.78102	[0, -2, -1, -2, -1, -2, -1, 0, -2, -2]
+contradictious	-1.9	1.04403	[-2, -3, 0, -3, -3, -1, -2, -1, -1, -3]
+contradictor	-1.0	0.63246	[-1, -1, -1, -2, -1, -2, 0, 0, -1, -1]
+contradictories	-0.5	1.11803	[-1, 0, -1, -2, 2, 1, -1, -1, -1, -1]
+contradictorily	-0.9	1.3	[0, -1, -1, -1, -3, -1, 1, 1, -3, -1]
+contradictoriness	-1.4	0.4899	[-2, -1, -1, -1, -2, -1, -1, -2, -2, -1]
+contradictors	-1.6	0.66332	[-1, -2, -1, -2, -1, -1, -3, -1, -2, -2]
+contradictory	-1.4	0.4899	[-1, -2, -1, -2, -1, -1, -1, -1, -2, -2]
+contradicts	-1.4	0.66332	[-1, -2, -1, -2, -2, -2, 0, -1, -1, -2]
+controversial	-0.8	0.87178	[0, 0, -1, 1, -2, -1, -1, -1, -1, -2]
+controversially	-1.1	1.04403	[0, -1, -1, -2, -1, -2, -1, 1, -3, -1]
+convince	1.0	0.89443	[-1, 2, 2, 1, 1, 0, 1, 1, 2, 1]
+convinced	1.7	0.64031	[2, 1, 1, 2, 1, 2, 2, 2, 1, 3]
+convincer	0.6	0.66332	[2, 0, 1, 0, 1, 1, 0, 0, 0, 1]
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+dearness	2.0	0.7746	[1, 1, 2, 3, 2, 2, 2, 3, 1, 3]
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+deary	1.9	0.83066	[3, 2, 2, 1, 2, 2, 3, 2, 0, 2]
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+debt	-1.5	1.0247	[-2, -1, -2, -3, 1, -2, -2, -1, -1, -2]
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+decayer	-1.6	0.4899	[-2, -2, -2, -1, -2, -1, -1, -1, -2, -2]
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+deceive	-1.7	0.64031	[-1, -2, -2, -1, -2, -1, -1, -3, -2, -2]
+deceived	-1.9	1.3	[1, -3, -3, -1, -1, -2, -2, -2, -4, -2]
+deceives	-1.6	1.56205	[-1, 2, -2, -2, -3, -2, 0, -2, -4, -2]
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+deception	-1.9	1.04403	[-1, -2, -2, -4, -2, 0, -2, -1, -3, -2]
+decisive	0.9	0.83066	[2, 2, 0, 1, -1, 1, 1, 1, 1, 1]
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+defeated	-2.1	0.83066	[-1, -2, -1, -2, -3, -2, -2, -2, -2, -4]
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+defeaters	-0.9	0.9434	[-2, 0, -1, -2, -2, -1, 0, -1, 1, -1]
+defeating	-1.6	0.66332	[-2, -2, -1, -1, -1, -1, -2, -2, -3, -1]
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+defeature	-1.9	1.22066	[1, -2, -2, -2, -2, -1, -2, -3, -4, -2]
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+defect	-1.4	0.8	[-2, -1, -2, -1, 0, -2, -3, -1, -1, -1]
+defected	-1.7	0.64031	[-3, -2, -2, -2, -1, -1, -1, -2, -1, -2]
+defecting	-1.8	0.6	[-2, -1, -2, -2, -2, -1, -3, -1, -2, -2]
+defection	-1.4	0.66332	[-1, -2, -1, -2, 0, -1, -2, -2, -2, -1]
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+defectively	-2.1	0.83066	[-1, -3, -2, -1, -3, -2, -1, -3, -2, -3]
+defectiveness	-1.8	0.74833	[-1, -1, -2, -2, -2, -3, -1, -1, -2, -3]
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+defector	-1.9	0.53852	[-2, -3, -2, -2, -1, -2, -1, -2, -2, -2]
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+defenselessness	-1.3	1.18743	[-3, -1, -3, 0, -2, -1, -1, -2, 1, -1]
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+deferring	-0.7	0.64031	[0, 0, -2, -1, -1, -1, -1, 0, -1, 0]
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+deficit	-1.7	0.78102	[-3, -3, -2, -1, -2, -2, -1, -1, -1, -1]
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+degrading	-2.8	0.87178	[-3, -3, -2, -3, -4, -2, -3, -4, -3, -1]
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+deject	-2.2	0.6	[-2, -3, -2, -3, -2, -2, -3, -2, -1, -2]
+dejected	-2.2	0.74833	[-2, -1, -2, -3, -2, -2, -2, -2, -2, -4]
+dejecting	-2.3	0.64031	[-2, -2, -3, -2, -3, -2, -1, -2, -3, -3]
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+desperation	-2.0	1.0	[-2, -1, -1, -2, -3, -3, -1, -4, -1, -2]
+desperations	-2.2	1.66132	[-1, -4, -2, -4, -4, -1, -1, -2, 1, -4]
+despise	-1.4	1.35647	[-2, -3, -1, -2, -1, 1, -3, 1, -2, -2]
+despised	-1.7	1.48661	[-2, -1, -3, -2, -3, 1, -3, 1, -2, -3]
+despisement	-2.4	0.91652	[-3, -3, -2, -1, -3, -1, -4, -2, -2, -3]
+despisements	-2.5	1.0247	[-2, -2, -3, -2, 0, -3, -4, -3, -3, -3]
+despiser	-1.8	1.07703	[-2, -1, -3, 1, -2, -2, -3, -2, -2, -2]
+despisers	-1.6	1.35647	[-3, -3, -1, -3, -2, -1, -1, 1, 0, -3]
+despises	-2.0	1.26491	[-3, -1, -3, 1, -2, -1, -3, -2, -3, -3]
+despising	-2.7	0.9	[-4, -3, -3, -4, -1, -2, -3, -2, -2, -3]
+despondent	-2.1	0.53852	[-2, -2, -2, -3, -2, -2, -1, -3, -2, -2]
+destroy	-2.5	0.67082	[-2, -3, -3, -1, -3, -3, -3, -2, -2, -3]
+destroyed	-2.2	0.87178	[-1, -3, -3, -2, -1, -2, -1, -3, -3, -3]
+destroyer	-2.0	0.89443	[-2, -3, -3, -3, -1, -2, -2, -2, 0, -2]
+destroyers	-2.3	0.78102	[-1, -3, -3, -3, -2, -2, -3, -3, -1, -2]
+destroying	-2.6	0.91652	[-2, -4, -4, -2, -1, -3, -2, -3, -2, -3]
+destroys	-2.6	0.4899	[-3, -3, -3, -2, -2, -2, -3, -3, -2, -3]
+destruct	-2.4	0.4899	[-3, -3, -3, -2, -2, -2, -3, -2, -2, -2]
+destructed	-1.9	1.04403	[-4, -1, -2, -2, -2, -1, -3, -2, 0, -2]
+destructibility	-1.8	1.07703	[-1, -2, -1, -1, -2, -3, -2, 0, -4, -2]
+destructible	-1.5	1.11803	[-2, -2, -2, -1, 1, -1, -3, -1, -3, -1]
+destructing	-2.5	0.67082	[-2, -3, -2, -3, -2, -2, -2, -3, -2, -4]
+destruction	-2.7	0.9	[-4, -3, -4, -3, -2, -2, -3, -1, -2, -3]
+destructionist	-2.6	0.8	[-3, -4, -2, -2, -2, -3, -3, -1, -3, -3]
+destructionists	-2.1	0.53852	[-3, -1, -2, -2, -3, -2, -2, -2, -2, -2]
+destructions	-2.3	0.78102	[-3, -2, -2, -2, -1, -3, -4, -2, -2, -2]
+destructive	-3.0	0.63246	[-3, -4, -3, -2, -3, -3, -3, -2, -4, -3]
+destructively	-2.4	0.91652	[-2, -3, -1, -4, -2, -3, -3, -3, -1, -2]
+destructiveness	-2.4	0.91652	[-3, -3, -2, -4, -1, -2, -3, -2, -1, -3]
+destructivity	-2.2	1.53623	[2, -3, -3, -4, -3, -2, -2, -2, -2, -3]
+destructs	-2.4	0.91652	[-2, -1, -2, -4, -4, -2, -3, -2, -2, -2]
+detached	-0.5	1.20416	[-1, 2, -1, -1, -2, 0, 1, -2, -1, 0]
+detain	-1.8	0.9798	[-3, -1, -2, -2, -4, -2, -1, -1, -1, -1]
+detained	-1.7	0.9	[-1, -1, -1, -1, -1, -2, -2, -2, -2, -4]
+detention	-1.5	0.67082	[-1, -2, -1, -2, -1, -1, -3, -2, -1, -1]
+determinable	0.9	0.7	[2, 1, 1, 1, 0, 1, 2, 0, 0, 1]
+determinableness	0.2	1.07703	[0, 0, 0, 1, 0, 1, -1, 2, -2, 1]
+determinably	0.9	0.83066	[2, 0, 1, 1, 0, 1, 2, 2, 0, 0]
+determinacy	1.0	1.0	[0, 0, 0, 3, 1, 1, 2, 1, 0, 2]
+determinant	0.2	0.6	[0, 1, -1, 0, 1, 1, 0, 0, 0, 0]
+determinantal	-0.3	1.41774	[0, 0, 0, -4, 0, -1, 0, 0, 2, 0]
+determinate	0.8	0.87178	[2, 1, 0, 0, 0, 2, 2, 0, 1, 0]
+determinately	1.2	0.6	[1, 2, 0, 1, 1, 1, 2, 1, 2, 1]
+determinateness	1.1	0.9434	[1, 1, 1, 0, 0, 2, 3, 1, 0, 2]
+determination	1.7	0.78102	[2, 3, 1, 1, 1, 2, 1, 1, 2, 3]
+determinations	0.8	1.16619	[0, 3, 1, 0, 1, 3, 0, 0, 0, 0]
+determinative	1.1	1.04403	[2, 0, 3, 2, 1, 1, 0, 0, 2, 0]
+determinatives	0.9	1.3	[2, 0, -2, 1, 2, 2, 2, 0, 0, 2]
+determinator	1.1	1.04403	[3, 0, 1, 0, 1, 0, 2, 2, 0, 2]
+determined	1.4	1.35647	[-2, 1, 3, 2, 2, 2, 3, 1, 1, 1]
+devastate	-3.1	0.9434	[-4, -4, -1, -4, -4, -3, -3, -3, -2, -3]
+devastated	-3.0	0.89443	[-4, -3, -3, -4, -3, -1, -3, -4, -3, -2]
+devastates	-2.8	0.9798	[-4, -3, -2, -4, -2, -1, -3, -4, -3, -2]
+devastating	-3.3	0.9	[-4, -3, -4, -4, -1, -4, -3, -3, -3, -4]
+devastatingly	-2.4	1.28062	[-3, -4, -3, 0, -3, 0, -2, -3, -3, -3]
+devastation	-1.8	2.13542	[-1, -1, -3, -3, -4, -3, -4, 2, 2, -3]
+devastations	-1.9	1.92094	[-3, -3, -2, -2, 1, -1, 2, -4, -4, -3]
+devastative	-3.2	1.16619	[-4, -3, 0, -4, -4, -3, -3, -4, -3, -4]
+devastator	-2.8	0.74833	[-3, -3, -2, -2, -3, -2, -3, -4, -2, -4]
+devastators	-2.9	1.22066	[-3, -2, -3, -4, -4, -4, 0, -3, -2, -4]
+devil	-3.4	0.8	[-4, -3, -4, -4, -4, -4, -2, -3, -2, -4]
+deviled	-1.6	1.0198	[-1, -2, 0, -4, -1, -2, -2, -2, -1, -1]
+devilfish	-0.8	1.07703	[-2, -3, -1, 0, 0, 0, 0, -2, 0, 0]
+devilfishes	-0.6	1.0198	[-3, 0, -2, 0, 0, 0, 0, -1, 0, 0]
+deviling	-2.2	0.87178	[-1, -3, -1, -2, -3, -2, -2, -4, -2, -2]
+devilish	-2.1	1.04403	[-1, -2, -4, -1, -1, -2, -2, -4, -2, -2]
+devilishly	-1.6	0.8	[-2, -2, -3, -1, -2, -2, 0, -2, -1, -1]
+devilishness	-2.3	0.9	[-4, -1, -4, -2, -2, -2, -2, -2, -2, -2]
+devilkin	-2.4	0.91652	[-3, -1, -2, -3, -2, -4, -2, -3, -3, -1]
+devilled	-2.3	1.1	[-3, -1, -2, -3, 0, -4, -2, -3, -2, -3]
+devilling	-1.8	1.249	[-3, -1, -1, -2, -2, -3, -4, -2, 0, 0]
+devilment	-1.9	0.9434	[-2, -1, -2, -1, -3, -2, -2, -1, -1, -4]
+devilments	-1.1	0.7	[-2, -1, -2, -2, -1, 0, 0, -1, -1, -1]
+devilries	-1.6	1.35647	[-1, -1, -2, -4, -3, 0, -2, 0, 0, -3]
+devilry	-2.8	1.249	[-4, -3, 0, -2, -2, -2, -3, -4, -4, -4]
+devils	-2.7	0.9	[-3, -1, -3, -2, -2, -3, -4, -3, -2, -4]
+deviltries	-1.5	1.11803	[-1, -2, 1, -2, 0, -2, -2, -3, -2, -2]
+deviltry	-2.8	1.32665	[-4, -4, -3, -3, -3, -3, 1, -3, -3, -3]
+devilwood	-0.8	1.07703	[0, -1, -2, 0, 0, 0, 0, -3, -2, 0]
+devilwoods	-1.0	0.7746	[-2, 0, -2, -1, -1, 0, -1, -2, 0, -1]
+devote	1.4	1.28062	[3, 0, 2, -1, 0, 3, 2, 2, 1, 2]
+devoted	1.7	1.34536	[2, -1, 3, 2, 1, 0, 1, 3, 3, 3]
+devotedly	1.6	1.35647	[1, 1, 2, 2, 3, 2, 2, -2, 2, 3]
+devotedness	2.0	1.0	[0, 3, 2, 1, 3, 2, 2, 3, 1, 3]
+devotee	1.6	1.11355	[1, 3, 0, 2, 1, 2, 1, 1, 4, 1]
+devotees	0.5	1.0247	[0, 0, 3, 0, 0, 0, 2, 0, 0, 0]
+devotement	1.5	1.36015	[2, -1, 3, 2, -1, 1, 2, 3, 2, 2]
+devotements	1.1	1.04403	[0, 1, 0, 0, 0, 2, 2, 2, 3, 1]
+devotes	1.6	0.91652	[2, 3, 0, 2, 2, 3, 1, 1, 1, 1]
+devoting	2.1	0.7	[2, 2, 3, 1, 2, 3, 2, 3, 1, 2]
+devotion	2.0	1.0	[2, 0, 1, 2, 4, 3, 2, 2, 2, 2]
+devotional	1.2	1.16619	[0, 1, 0, 2, 2, 1, 0, 0, 3, 3]
+devotionally	2.2	0.4	[2, 2, 2, 3, 2, 3, 2, 2, 2, 2]
+devotionals	1.2	1.07703	[3, 1, 1, 0, -1, 2, 2, 2, 1, 1]
+devotions	1.8	0.74833	[2, 3, 1, 2, 1, 3, 1, 2, 1, 2]
+diamond	1.4	1.42829	[0, 0, 2, 0, 1, 3, 1, 3, 0, 4]
+dick	-2.3	1.18743	[-2, -3, -4, -2, 0, -4, -2, -1, -3, -2]
+dickhead	-3.1	0.53852	[-4, -3, -3, -3, -4, -2, -3, -3, -3, -3]
+die	-2.9	0.9434	[-4, -3, -1, -2, -4, -3, -3, -3, -2, -4]
+died	-2.6	1.28062	[-3, -1, -3, -4, -2, -4, -3, -4, -2, 0]
+difficult	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -1, -2]
+difficulties	-1.2	0.4	[-1, -2, -1, -1, -1, -2, -1, -1, -1, -1]
+difficultly	-1.7	0.45826	[-1, -2, -1, -2, -2, -1, -2, -2, -2, -2]
+difficulty	-1.4	0.66332	[-2, -2, -2, -2, 0, -1, -1, -2, -1, -1]
+diffident	-1.0	0.44721	[-1, -1, -1, -1, -1, 0, -2, -1, -1, -1]
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+dignify	1.8	0.74833	[1, 2, 2, 1, 3, 3, 1, 2, 2, 1]
+dignifying	2.1	1.04403	[1, 1, 1, 3, 1, 4, 2, 3, 2, 3]
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+dilemma	-0.7	1.48661	[2, -1, -2, -2, -1, -1, 2, 0, -2, -2]
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+dire	-2.0	1.26491	[-2, -3, -3, -2, -3, -1, -1, 1, -3, -3]
+direful	-3.1	0.83066	[-3, -3, -3, -3, -4, -1, -4, -3, -4, -3]
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+dirtier	-1.4	0.4899	[-2, -1, -1, -2, -1, -2, -1, -1, -2, -1]
+dirtiest	-2.4	1.0198	[-4, -3, -2, -1, -2, -3, -1, -2, -4, -2]
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+disabling	-2.1	0.53852	[-2, -1, -3, -3, -2, -2, -2, -2, -2, -2]
+disadvantage	-1.8	0.4	[-2, -2, -1, -2, -2, -1, -2, -2, -2, -2]
+disadvantaged	-1.7	0.64031	[-2, -2, -3, -1, -2, -2, -2, -1, -1, -1]
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+disadvantageously	-2.1	0.83066	[-2, -4, -1, -2, -1, -2, -2, -2, -3, -2]
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+disadvantages	-1.7	0.64031	[-2, -2, -3, -1, -2, -2, -2, -1, -1, -1]
+disagree	-1.6	0.4899	[-1, -2, -1, -1, -2, -2, -2, -2, -1, -2]
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+disagreeably	-1.5	0.67082	[-3, -2, -1, -1, -1, -2, -1, -2, -1, -1]
+disagreed	-1.3	0.64031	[-1, -2, -1, -1, -2, 0, -1, -2, -1, -2]
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+disagreement	-1.5	0.67082	[-2, -1, -1, -1, -1, -1, -1, -3, -2, -2]
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+disappeared	-0.9	0.7	[-2, 0, -1, -1, 0, 0, -2, -1, -1, -1]
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+disappointed	-2.1	0.83066	[-1, -3, -2, -2, -3, -1, -1, -2, -3, -3]
+disappointedly	-1.7	0.78102	[-3, -1, -3, -1, -2, -1, -1, -2, -2, -1]
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+disappointingly	-1.9	0.7	[-2, -1, -1, -3, -2, -3, -2, -2, -1, -2]
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+disappointments	-2.0	1.09545	[-1, -2, -4, -3, -2, -2, -3, 0, -2, -1]
+disappoints	-1.6	0.4899	[-2, -1, -1, -1, -2, -1, -2, -2, -2, -2]
+disaster	-3.1	0.83066	[-2, -4, -4, -3, -3, -2, -4, -3, -2, -4]
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+discard	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -1, -2, -1]
+discarded	-1.4	0.91652	[-1, -1, -1, -1, 0, -1, -2, -3, -3, -1]
+discarding	-0.7	0.45826	[-1, 0, -1, -1, -1, 0, -1, 0, -1, -1]
+discards	-1.0	0.63246	[0, -1, -1, -1, -2, 0, -2, -1, -1, -1]
+discomfort	-1.8	0.6	[-2, -2, -2, -1, -1, -3, -2, -2, -1, -2]
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+discomforting	-1.6	1.11355	[-1, -2, -1, -1, -2, 1, -3, -2, -3, -2]
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+disconsolation	-1.7	0.45826	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -2]
+discontented	-1.8	0.9798	[-1, -3, -1, -2, -4, -2, -1, -2, -1, -1]
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+discouragement	-2.0	0.89443	[-4, -1, -2, -2, -1, -1, -3, -2, -2, -2]
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+discourager	-1.7	0.78102	[-2, -1, -3, -2, -1, -3, -1, -2, -1, -1]
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+discouraging	-1.9	0.7	[-2, -2, -2, -3, -1, -1, -2, -1, -2, -3]
+discouragingly	-1.8	0.87178	[-2, -1, -3, -1, -1, -3, -2, -1, -3, -1]
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+disgrace	-2.2	0.74833	[-2, -4, -1, -2, -2, -2, -2, -3, -2, -2]
+disgraced	-2.0	0.44721	[-3, -2, -2, -2, -1, -2, -2, -2, -2, -2]
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+disguised	-1.1	1.04403	[-3, 0, 0, -1, -1, 0, -3, -1, -1, -1]
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+drained	-1.5	0.5	[-1, -1, -2, -2, -1, -2, -1, -2, -1, -2]
+dread	-2.0	0.63246	[-2, -3, -2, -2, -2, -2, -3, -1, -1, -2]
+dreaded	-2.7	0.64031	[-2, -3, -3, -3, -4, -3, -2, -2, -2, -3]
+dreadful	-1.9	1.86815	[-4, -2, -2, 2, -1, -4, -1, 0, -3, -4]
+dreadfully	-2.7	1.26886	[-4, -4, -3, -4, -3, -1, -2, -1, -1, -4]
+dreadfulness	-3.2	0.87178	[-3, -4, -2, -3, -4, -4, -2, -2, -4, -4]
+dreadfuls	-2.4	1.2	[-4, -3, -3, -2, -3, -2, -4, 0, -1, -2]
+dreading	-2.4	0.8	[-3, -2, -2, -2, -2, -2, -3, -4, -3, -1]
+dreadlock	-0.4	0.66332	[0, 0, 0, 0, 0, -1, -2, 0, -1, 0]
+dreadlocks	-0.2	0.9798	[0, 0, 0, 0, 0, -1, -2, 2, 0, -1]
+dreadnought	-0.6	1.35647	[-2, 0, 0, 0, -3, 0, -1, -2, 0, 2]
+dreadnoughts	-0.4	0.66332	[0, -1, -1, 0, 0, 0, 0, 0, -2, 0]
+dreads	-1.4	1.42829	[0, -1, 0, 0, -3, -3, 0, -4, -2, -1]
+dream	1.0	1.18322	[0, 1, 2, 0, 0, 3, 0, 3, 1, 0]
+dreams	1.7	1.1	[2, 2, 3, 0, 1, 1, 1, 4, 1, 2]
+dreary	-1.4	0.4899	[-1, -1, -2, -1, -1, -2, -2, -1, -2, -1]
+droopy	-0.8	0.74833	[-1, -1, 0, -1, -2, 0, 0, -1, 0, -2]
+drop	-1.1	0.53852	[0, -1, -1, -1, -2, -1, -2, -1, -1, -1]
+drown	-2.7	1.00499	[-4, -2, -2, -4, -4, -2, -3, -1, -3, -2]
+drowned	-2.9	0.7	[-2, -3, -3, -3, -2, -4, -4, -2, -3, -3]
+drowns	-2.2	1.6	[-3, -3, -3, -4, -2, -3, -1, -2, 2, -3]
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+dubious	-1.5	0.5	[-1, -2, -2, -1, -1, -2, -1, -1, -2, -2]
+dud	-1.0	0.89443	[-1, -1, -1, 0, -3, 0, -1, 0, -1, -2]
+dull	-1.7	0.45826	[-2, -2, -2, -1, -2, -2, -2, -1, -1, -2]
+dullard	-1.6	0.66332	[-2, -1, -1, -2, -2, -1, -1, -2, -1, -3]
+dullards	-1.8	0.87178	[-1, -3, -1, -1, -3, -1, -1, -2, -3, -2]
+dulled	-1.5	0.5	[-2, -1, -2, -1, -1, -1, -2, -2, -1, -2]
+duller	-1.7	0.64031	[-3, -1, -2, -2, -2, -1, -2, -1, -1, -2]
+dullest	-1.7	1.00499	[-1, -4, -1, -1, -2, -3, -2, -1, -1, -1]
+dulling	-1.1	0.7	[-1, -2, 0, -1, -2, -2, 0, -1, -1, -1]
+dullish	-1.1	0.53852	[-2, -1, -1, -1, -1, -1, -1, -1, 0, -2]
+dullness	-1.4	0.8	[-1, -1, -1, -1, -1, -1, -3, -1, -3, -1]
+dullnesses	-1.9	1.04403	[-3, -2, -1, -1, -3, -1, -4, -1, -2, -1]
+dulls	-1.0	0.44721	[-1, -1, -1, -1, -1, -1, 0, -1, -1, -2]
+dullsville	-2.4	0.8	[-2, -2, -4, -3, -2, -2, -3, -2, -3, -1]
+dully	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -2]
+dumb	-2.3	0.9	[-4, -2, -2, -2, -2, -2, -4, -2, -2, -1]
+dumbass	-2.6	1.0198	[-3, -3, -4, -4, -1, -2, -3, -3, -1, -2]
+dumbbell	-0.8	0.9798	[0, -1, -3, -2, 0, -1, 0, 0, -1, 0]
+dumbbells	-0.2	0.4	[0, -1, 0, 0, 0, 0, 0, -1, 0, 0]
+dumbcane	-0.3	0.45826	[0, 0, 0, 0, 0, -1, -1, 0, -1, 0]
+dumbcanes	-0.6	1.2	[0, 0, -1, -1, -1, 2, 0, -1, -3, -1]
+dumbed	-1.4	0.4899	[-2, -1, -2, -2, -2, -1, -1, -1, -1, -1]
+dumber	-1.5	0.5	[-2, -1, -2, -1, -2, -1, -1, -2, -2, -1]
+dumbest	-2.3	1.00499	[-3, -1, -3, -4, -2, -1, -2, -3, -1, -3]
+dumbfound	-0.1	1.92094	[3, -2, -1, -1, 1, 1, -3, 3, -1, -1]
+dumbfounded	-1.6	1.11355	[-2, 0, -2, 0, -2, -1, -4, -1, -2, -2]
+dumbfounder	-1.0	0.89443	[-2, 0, 0, 0, -2, -1, -2, 0, -2, -1]
+dumbfounders	-1.0	0.89443	[-1, -3, -1, 0, -2, 0, -1, 0, -1, -1]
+dumbfounding	-0.8	0.74833	[-1, -2, 0, -1, -1, 0, 0, -1, 0, -2]
+dumbfounds	-0.3	1.26886	[0, -1, -1, 0, 0, -1, -1, -2, 0, 3]
+dumbhead	-2.6	0.66332	[-3, -4, -3, -2, -2, -3, -3, -2, -2, -2]
+dumbheads	-1.9	0.83066	[-2, -2, -2, -1, -2, -1, -2, -4, -1, -2]
+dumbing	-0.5	1.0247	[-1, 2, -1, 0, -1, -2, -1, 0, 0, -1]
+dumbly	-1.3	1.00499	[-2, -1, -2, -3, 1, -2, -1, -1, -1, -1]
+dumbness	-1.9	0.53852	[-2, -2, -2, -2, -2, -3, -2, -2, -1, -1]
+dumbs	-1.5	0.67082	[-1, -1, -1, -3, -2, -1, -2, -1, -2, -1]
+dumbstruck	-1.0	1.34164	[-1, -2, 0, 0, -2, 1, -3, 1, -2, -2]
+dumbwaiter	0.2	1.07703	[0, 0, 0, 0, 2, 0, 2, 0, -2, 0]
+dumbwaiters	-0.1	0.3	[0, 0, 0, 0, 0, 0, -1, 0, 0, 0]
+dump	-1.6	0.91652	[-3, -2, -1, -2, -1, -3, -2, -1, -1, 0]
+dumpcart	-0.6	0.8	[0, -2, -1, 0, 0, 0, -1, 0, -2, 0]
+dumped	-1.7	0.78102	[-2, -3, -2, -1, -1, -1, -3, -2, -1, -1]
+dumper	-1.2	0.87178	[-2, -3, -1, -1, -1, -2, 0, -1, 0, -1]
+dumpers	-0.8	0.6	[0, 0, -2, -1, -1, 0, -1, -1, -1, -1]
+dumpier	-1.4	0.66332	[-2, -1, -2, -1, -1, -2, 0, -2, -1, -2]
+dumpiest	-1.6	1.35647	[-1, -2, -2, -3, -2, -4, 1, 0, -1, -2]
+dumpiness	-1.2	0.6	[-2, -1, 0, -1, -1, -2, -1, -2, -1, -1]
+dumping	-1.3	1.1	[-3, -2, -2, 0, -2, -1, -1, 1, -1, -2]
+dumpings	-1.1	0.83066	[-2, 0, -1, -1, 0, -1, -2, -2, 0, -2]
+dumpish	-1.8	0.6	[-2, -1, -2, -3, -2, -2, -1, -2, -2, -1]
+dumpling	0.4	0.91652	[0, 0, 1, 0, -1, 2, 2, 0, 0, 0]
+dumplings	-0.3	1.26886	[0, 0, 0, 0, 2, 0, 0, 0, -2, -3]
+dumps	-1.7	0.9	[-3, -2, -3, -1, -1, -3, -1, -1, -1, -1]
+dumpster	-0.6	0.91652	[0, -2, 0, -2, 0, 0, 0, -2, 0, 0]
+dumpsters	-1.0	0.89443	[0, -1, 0, -2, -2, -2, 0, 0, -1, -2]
+dumpy	-1.7	0.78102	[-3, -2, -3, -1, -1, -2, -2, -1, -1, -1]
+dupe	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -2, -1, -2, -1]
+duped	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -1, -2, -2]
+dwell	0.5	0.92195	[2, 1, -1, 0, -1, 1, 1, 1, 1, 0]
+dwelled	0.4	0.66332	[2, 0, 0, 0, 0, 1, 1, 0, 0, 0]
+dweller	0.3	0.64031	[2, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+dwellers	-0.3	0.9	[-3, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+dwelling	0.1	0.53852	[0, 1, 0, 1, 0, 0, 0, -1, 0, 0]
+dwells	-0.1	0.53852	[0, 0, 0, 0, -1, 1, -1, 0, 0, 0]
+dynamic	1.6	0.8	[1, 1, 1, 3, 1, 1, 2, 3, 2, 1]
+dynamical	1.2	0.87178	[1, 2, 0, 1, 0, 2, 2, 2, 2, 0]
+dynamically	1.5	1.0247	[2, 0, 3, 2, 0, 0, 2, 2, 2, 2]
+dynamics	1.1	1.13578	[2, 3, 0, 0, 0, 2, 2, 0, 2, 0]
+dynamism	1.6	1.11355	[0, 2, 0, 2, 0, 2, 3, 3, 2, 2]
+dynamisms	1.2	0.9798	[2, 0, 2, 0, 0, 2, 2, 2, 0, 2]
+dynamist	1.4	1.0198	[0, 2, 0, 2, 0, 1, 3, 2, 2, 2]
+dynamistic	1.5	1.0247	[3, 1, 1, 2, 1, 3, 2, 0, 2, 0]
+dynamists	0.9	0.83066	[1, 0, 0, 0, 0, 2, 2, 1, 2, 1]
+dynamite	0.7	2.2383	[-3, 2, 3, 1, 2, 0, 2, 2, 2, -4]
+dynamited	-0.9	1.04403	[0, 0, 0, -1, -1, 0, -2, 0, -2, -3]
+dynamiter	-1.2	0.87178	[-1, 0, -1, -1, -2, 0, -1, -1, -2, -3]
+dynamiters	0.4	1.42829	[0, 0, 0, -3, 1, 0, 2, 2, 2, 0]
+dynamites	-0.3	1.73494	[0, 0, 4, -1, -1, 0, 0, 0, -2, -3]
+dynamitic	0.9	1.3	[2, 0, 1, -2, 2, 1, 1, 3, 0, 1]
+dynamiting	0.2	1.32665	[-2, 0, 0, 2, -1, -1, 0, 2, 2, 0]
+dynamometer	0.3	0.64031	[0, 0, 0, 0, 1, 0, 0, 2, 0, 0]
+dynamometers	0.3	0.45826	[0, 0, 0, 0, 0, 1, 0, 1, 1, 0]
+dynamometric	0.3	0.9	[0, 0, 0, 0, 0, 2, 0, 0, 2, -1]
+dynamometry	0.6	1.28062	[-2, 0, 0, 0, 0, 2, 2, 2, 0, 2]
+dynamos	0.3	0.64031	[1, 0, 0, 0, 0, 0, 0, 0, 2, 0]
+dynamotor	0.6	0.91652	[0, 2, 0, 0, 0, 0, 2, 0, 2, 0]
+dysfunction	-1.8	0.6	[-2, -3, -2, -1, -2, -1, -2, -1, -2, -2]
+eager	1.5	0.67082	[1, 3, 1, 2, 2, 2, 1, 1, 1, 1]
+eagerly	1.6	0.66332	[0, 1, 2, 2, 2, 2, 2, 1, 2, 2]
+eagerness	1.7	0.45826	[2, 2, 2, 2, 1, 1, 2, 2, 2, 1]
+eagers	1.6	0.66332	[2, 2, 3, 1, 2, 1, 1, 1, 2, 1]
+earnest	2.3	0.64031	[3, 2, 3, 1, 2, 2, 2, 3, 3, 2]
+ease	1.5	0.92195	[1, 1, 1, 0, 2, 1, 2, 3, 3, 1]
+eased	1.2	0.74833	[2, 0, 1, 0, 2, 2, 1, 1, 1, 2]
+easeful	1.5	1.0247	[2, 1, 1, 2, 1, 0, 3, 2, 0, 3]
+easefully	1.4	0.4899	[2, 2, 1, 1, 1, 1, 2, 2, 1, 1]
+easel	0.3	0.45826	[0, 0, 0, 0, 1, 1, 0, 0, 0, 1]
+easement	1.6	0.91652	[0, 1, 2, 3, 2, 1, 2, 1, 3, 1]
+easements	0.4	1.11355	[0, 0, 0, 1, 2, -2, 1, 0, 2, 0]
+eases	1.3	0.78102	[2, 0, 1, 0, 2, 2, 2, 1, 1, 2]
+easier	1.8	0.9798	[1, 1, 2, 2, 4, 3, 2, 1, 1, 1]
+easiest	1.8	1.07703	[2, 4, 1, 3, 2, 0, 2, 2, 1, 1]
+easily	1.4	0.4899	[2, 1, 1, 2, 1, 2, 1, 2, 1, 1]
+easiness	1.6	0.66332	[2, 1, 1, 2, 3, 2, 1, 1, 2, 1]
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+easy	1.9	1.04403	[1, 4, 2, 1, 1, 3, 1, 3, 2, 1]
+easygoing	1.3	0.45826	[1, 1, 1, 1, 1, 1, 2, 2, 2, 1]
+easygoingness	1.5	0.67082	[1, 2, 1, 2, 1, 3, 1, 2, 1, 1]
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+ecstasy	2.9	1.75784	[4, 3, 3, 4, 4, 2, -2, 3, 4, 4]
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+ecstatically	2.8	1.93907	[3, 4, -1, 4, 4, 4, -1, 3, 4, 4]
+ecstatics	2.9	0.83066	[1, 3, 4, 4, 3, 3, 3, 2, 3, 3]
+eerie	-1.5	0.67082	[-1, -1, -2, -2, -1, -1, -2, -1, -3, -1]
+eery	-0.9	1.04403	[-3, -1, -2, -1, -2, 0, 0, 0, 0, 0]
+effective	2.1	0.83066	[2, 2, 2, 1, 3, 4, 2, 1, 2, 2]
+effectively	1.9	0.7	[1, 2, 1, 2, 2, 1, 3, 3, 2, 2]
+efficiencies	1.6	0.4899	[2, 1, 1, 2, 2, 2, 1, 2, 2, 1]
+efficiency	1.5	0.5	[2, 1, 2, 2, 1, 2, 1, 1, 2, 1]
+efficient	1.8	0.9798	[1, 2, 1, 1, 2, 3, 3, 0, 2, 3]
+efficiently	1.7	0.78102	[1, 3, 2, 1, 3, 1, 1, 2, 2, 1]
+effin	-2.3	1.18743	[0, -3, -3, -3, -2, -1, -4, -1, -3, -3]
+egotism	-1.4	0.91652	[-2, -3, -1, -2, -2, 0, 0, -1, -2, -1]
+egotisms	-1.0	0.7746	[-1, -1, -1, -1, -1, 0, 0, -1, -3, -1]
+egotist	-2.3	0.9	[-2, -1, -2, -3, -4, -2, -3, -3, -1, -2]
+egotistic	-1.4	1.0198	[-2, -1, -1, -1, -2, 1, -3, -2, -1, -2]
+egotistical	-0.9	1.57797	[-1, -2, -2, -1, -2, 1, -3, 2, 1, -2]
+egotistically	-1.8	0.87178	[-2, -1, -1, -2, -1, -3, -3, -1, -1, -3]
+egotists	-1.7	0.78102	[-1, -2, 0, -2, -2, -2, -3, -1, -2, -2]
+elated	3.2	0.74833	[2, 4, 4, 3, 4, 3, 3, 2, 3, 4]
+elation	1.5	1.43178	[1, 2, -2, 2, 2, 3, 0, 3, 2, 2]
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+elegances	1.8	0.6	[2, 2, 1, 1, 2, 2, 2, 3, 2, 1]
+elegancies	1.6	1.0198	[2, 1, 2, 1, 1, 0, 4, 1, 2, 2]
+elegancy	2.1	0.53852	[3, 2, 2, 1, 2, 2, 3, 2, 2, 2]
+elegant	2.1	0.83066	[2, 2, 2, 1, 4, 1, 2, 3, 2, 2]
+elegantly	1.9	0.83066	[2, 1, 1, 3, 2, 2, 1, 3, 3, 1]
+embarrass	-1.2	1.66132	[-2, -2, -3, -1, -2, -2, 2, 2, -2, -2]
+embarrassable	-1.6	0.8	[-3, -2, -1, -3, -1, -1, -1, -2, -1, -1]
+embarrassed	-1.5	0.67082	[-2, -2, -1, -2, -1, -3, -1, -1, -1, -1]
+embarrassedly	-1.1	1.44568	[-2, -1, -2, -3, 1, -1, -1, -2, -2, 2]
+embarrasses	-1.7	0.78102	[-2, -3, -1, -2, -1, -3, -2, -1, -1, -1]
+embarrassing	-1.6	0.8	[-3, -1, -1, -1, -1, -2, -1, -2, -3, -1]
+embarrassingly	-1.7	0.64031	[-2, -1, -1, -2, -1, -2, -1, -3, -2, -2]
+embarrassment	-1.9	0.53852	[-2, -2, -1, -2, -2, -2, -2, -1, -3, -2]
+embarrassments	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -3]
+embittered	-0.4	1.35647	[1, -2, -1, 1, -2, 2, 0, -1, 0, -2]
+embrace	1.3	1.34536	[3, 2, 1, 3, 2, -1, 2, 1, -1, 1]
+emergency	-1.6	2.05913	[-3, -3, -3, -3, -4, 2, 1, -1, 1, -3]
+emotional	0.6	1.0198	[1, -1, 0, 0, 0, 2, 0, 2, 2, 0]
+empathetic	1.7	1.1	[-1, 3, 2, 2, 2, 1, 3, 1, 2, 2]
+emptied	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
+emptier	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
+emptiers	-0.7	0.78102	[0, 0, -1, 0, -1, -1, -2, 0, -2, 0]
+empties	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
+emptiest	-1.8	1.07703	[-1, -2, -2, -1, -1, -2, -3, 0, -4, -2]
+emptily	-1.0	1.41421	[-2, 2, -1, -1, -1, 0, -4, -1, -1, -1]
+emptiness	-1.9	0.7	[-2, -2, -3, -2, -2, -1, -1, -3, -1, -2]
+emptinesses	-1.5	1.11803	[-1, -1, -3, -1, -1, -1, -2, 0, -4, -1]
+emptins	-0.3	0.45826	[0, 0, 0, -1, 0, 0, 0, -1, -1, 0]
+empty	-0.8	0.74833	[-1, -1, -1, -1, -1, -1, -2, 0, -1, 1]
+emptying	-0.6	1.0198	[2, -1, -1, 0, -1, 0, -1, -1, -2, -1]
+enchanted	1.6	0.8	[1, 3, 1, 2, 1, 3, 1, 2, 1, 1]
+encourage	2.3	0.78102	[2, 1, 3, 2, 3, 4, 2, 2, 2, 2]
+encouraged	1.5	0.5	[1, 2, 2, 2, 2, 2, 1, 1, 1, 1]
+encouragement	1.8	0.9798	[2, 1, 2, 1, 1, 3, 1, 2, 4, 1]
+encouragements	2.1	0.7	[3, 2, 3, 2, 1, 2, 3, 2, 2, 1]
+encourager	1.5	0.5	[2, 1, 2, 1, 1, 2, 1, 1, 2, 2]
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+encourages	1.9	0.53852	[2, 2, 1, 2, 2, 1, 2, 2, 2, 3]
+encouraging	2.4	0.66332	[2, 3, 2, 3, 3, 2, 3, 2, 1, 3]
+encouragingly	2.0	0.7746	[1, 1, 1, 3, 2, 2, 2, 3, 2, 3]
+endorse	1.3	0.9	[0, 1, 0, 1, 3, 2, 2, 2, 1, 1]
+endorsed	1.0	0.89443	[1, 2, 0, 1, 1, 0, 1, 0, 3, 1]
+endorsement	1.3	0.9	[0, 1, 2, 2, 1, 2, 0, 1, 3, 1]
+endorses	1.4	0.4899	[1, 2, 1, 2, 1, 1, 1, 2, 2, 1]
+enemies	-2.2	0.6	[-2, -3, -1, -2, -2, -3, -2, -3, -2, -2]
+enemy	-2.5	0.92195	[-3, -2, -3, -3, -3, -4, -1, -3, -1, -2]
+energetic	1.9	0.53852	[2, 1, 3, 2, 2, 2, 1, 2, 2, 2]
+energetically	1.8	0.6	[2, 2, 1, 1, 2, 2, 3, 1, 2, 2]
+energetics	0.3	0.64031	[1, 0, 0, 0, 0, 0, 2, 0, 0, 0]
+energies	0.9	1.04403	[1, 0, 0, 2, 0, 1, 3, 2, 0, 0]
+energise	2.2	0.4	[2, 2, 2, 2, 2, 2, 3, 2, 3, 2]
+energised	2.1	0.53852	[2, 3, 1, 2, 2, 2, 3, 2, 2, 2]
+energises	2.2	0.6	[3, 3, 2, 2, 1, 3, 2, 2, 2, 2]
+energising	1.9	0.7	[2, 3, 1, 2, 2, 3, 2, 1, 1, 2]
+energization	1.6	0.66332	[1, 2, 1, 3, 1, 1, 2, 2, 2, 1]
+energizations	1.5	1.11803	[1, 0, 3, 1, 3, 0, 1, 1, 2, 3]
+energize	2.1	0.7	[2, 2, 2, 1, 3, 2, 3, 2, 3, 1]
+energized	2.3	0.64031	[3, 2, 3, 3, 3, 2, 2, 2, 1, 2]
+energizer	2.1	0.53852	[3, 2, 2, 2, 2, 2, 2, 3, 1, 2]
+energizers	1.7	0.9	[2, 0, 2, 3, 3, 1, 1, 2, 2, 1]
+energizes	2.1	0.53852	[3, 2, 3, 2, 2, 2, 2, 2, 1, 2]
+energizing	2.0	0.63246	[3, 3, 2, 1, 2, 2, 1, 2, 2, 2]
+energy	1.1	0.83066	[0, 2, 0, 2, 1, 1, 2, 1, 2, 0]
+engage	1.4	0.8	[1, 2, 3, 2, 1, 1, 0, 1, 2, 1]
+engaged	1.7	1.1	[1, 1, 2, 2, 1, 0, 2, 3, 4, 1]
+engagement	2.0	1.34164	[0, 0, 3, 4, 4, 2, 1, 2, 2, 2]
+engagements	0.6	0.8	[1, 0, 0, 2, 0, 2, 0, 0, 1, 0]
+engager	1.1	0.7	[1, 1, 0, 2, 1, 0, 2, 1, 2, 1]
+engagers	1.0	0.7746	[1, 1, 1, 0, 2, 1, 0, 2, 2, 0]
+engages	1.0	0.7746	[1, 1, 0, 2, 1, 0, 1, 2, 2, 0]
+engaging	1.4	0.4899	[2, 2, 1, 1, 2, 1, 1, 1, 1, 2]
+engagingly	1.5	0.67082	[1, 2, 3, 1, 1, 1, 1, 1, 2, 2]
+engrossed	0.6	1.49666	[0, 2, 0, 2, -2, 2, 3, -1, 0, 0]
+enjoy	2.2	0.6	[3, 2, 2, 2, 3, 2, 2, 3, 2, 1]
+enjoyable	1.9	0.53852	[3, 2, 2, 1, 2, 1, 2, 2, 2, 2]
+enjoyableness	1.9	1.13578	[2, 2, 2, 2, 1, 3, 3, 3, -1, 2]
+enjoyably	1.8	0.4	[2, 2, 2, 1, 2, 1, 2, 2, 2, 2]
+enjoyed	2.3	0.64031	[2, 2, 1, 3, 3, 3, 2, 2, 2, 3]
+enjoyer	2.2	0.6	[2, 2, 1, 3, 3, 2, 2, 2, 2, 3]
+enjoyers	2.2	0.74833	[2, 4, 2, 2, 2, 2, 2, 3, 2, 1]
+enjoying	2.4	0.66332	[2, 2, 2, 3, 3, 3, 1, 3, 2, 3]
+enjoyment	2.6	0.4899	[2, 3, 2, 3, 2, 3, 2, 3, 3, 3]
+enjoyments	2.0	0.7746	[3, 1, 1, 3, 2, 1, 2, 2, 2, 3]
+enjoys	2.3	0.45826	[2, 3, 2, 2, 2, 3, 2, 3, 2, 2]
+enlighten	2.3	1.1	[2, 2, 1, 3, 2, 1, 1, 4, 3, 4]
+enlightened	2.2	0.87178	[4, 2, 3, 1, 2, 2, 1, 3, 2, 2]
+enlightening	2.3	0.64031	[3, 2, 2, 2, 2, 2, 2, 4, 2, 2]
+enlightens	1.7	1.00499	[2, 1, 1, 1, 1, 2, 4, 1, 3, 1]
+ennui	-1.2	0.6	[-1, -1, -1, -2, -1, -1, -2, -1, 0, -2]
+enrage	-2.6	0.91652	[-3, -3, -3, -4, -1, -1, -3, -2, -3, -3]
+enraged	-1.7	1.79165	[-3, -3, -3, -3, 2, -1, -3, -1, 1, -3]
+enrages	-1.8	1.6	[-3, -3, -3, -3, 1, -1, -3, -1, 1, -3]
+enraging	-2.8	0.74833	[-4, -2, -3, -2, -2, -3, -3, -2, -4, -3]
+enrapture	3.0	0.63246	[2, 4, 3, 3, 4, 3, 3, 2, 3, 3]
+enslave	-3.1	0.9434	[-3, -4, -2, -4, -4, -2, -4, -2, -4, -2]
+enslaved	-1.7	2.41039	[3, -3, -3, -3, -4, -4, -4, 1, -1, 1]
+enslaves	-1.6	2.15407	[2, -2, -3, -2, -4, -4, -4, 1, -1, 1]
+ensure	1.6	0.91652	[2, 1, 3, 1, 1, 2, 3, 2, 0, 1]
+ensuring	1.1	0.9434	[0, 1, 3, 1, 1, 2, 1, 0, 2, 0]
+enterprising	2.3	0.78102	[3, 2, 1, 3, 3, 2, 1, 2, 3, 3]
+entertain	1.3	0.64031	[1, 2, 1, 1, 2, 1, 2, 0, 1, 2]
+entertained	1.7	0.64031	[1, 2, 2, 1, 2, 1, 1, 3, 2, 2]
+entertainer	1.6	1.2	[1, 4, 2, 2, 0, 0, 1, 3, 1, 2]
+entertainers	1.0	0.7746	[0, 1, 2, 2, 0, 0, 1, 1, 2, 1]
+entertaining	1.9	0.83066	[1, 2, 1, 1, 3, 2, 3, 2, 3, 1]
+entertainingly	1.9	0.53852	[2, 1, 2, 3, 2, 2, 1, 2, 2, 2]
+entertainment	1.8	0.9798	[2, 0, 4, 2, 2, 1, 2, 2, 1, 2]
+entertainments	2.3	1.18743	[3, 3, 3, 2, 1, 0, 3, 4, 1, 3]
+entertains	2.4	0.66332	[2, 2, 2, 2, 2, 3, 4, 3, 2, 2]
+enthral	0.4	1.42829	[2, 2, 0, 2, 0, -1, -2, 2, 0, -1]
+enthuse	1.6	0.66332	[1, 2, 1, 1, 3, 1, 2, 2, 2, 1]
+enthused	2.0	0.63246	[3, 3, 1, 2, 2, 2, 2, 1, 2, 2]
+enthuses	1.7	0.78102	[2, 3, 1, 2, 1, 3, 1, 1, 1, 2]
+enthusiasm	1.9	0.9434	[3, 3, 3, 2, 1, 0, 2, 1, 2, 2]
+enthusiasms	2.0	0.89443	[1, 3, 2, 2, 3, 2, 0, 2, 3, 2]
+enthusiast	1.5	0.67082	[1, 2, 2, 2, 0, 1, 1, 2, 2, 2]
+enthusiastic	2.2	0.9798	[1, 2, 3, 4, 2, 3, 2, 1, 1, 3]
+enthusiastically	2.6	0.66332	[3, 3, 3, 2, 3, 3, 3, 3, 2, 1]
+enthusiasts	1.4	0.91652	[1, 1, 0, 3, 3, 2, 1, 1, 1, 1]
+enthusing	1.9	0.7	[2, 1, 2, 1, 2, 3, 2, 1, 2, 3]
+entitled	1.1	0.83066	[2, 2, 1, 1, 2, 1, 1, -1, 1, 1]
+entrusted	0.8	1.46969	[3, 0, 2, 2, 1, 1, -1, 0, -2, 2]
+envied	-1.1	0.83066	[-1, -2, -2, 1, -2, -1, -1, -1, -1, -1]
+envier	-1.0	0.7746	[-1, -2, -2, -1, -1, 1, -1, -1, -1, -1]
+enviers	-1.1	1.13578	[-3, -1, 0, -3, -1, -1, -1, -1, 1, -1]
+envies	-0.8	0.9798	[-1, -2, -2, 1, -1, 1, -1, -1, -1, -1]
+envious	-1.1	0.83066	[-2, -1, -1, -1, -2, -1, -1, 1, -2, -1]
+envy	-1.1	0.83066	[-2, -1, -1, -2, -1, -1, -1, 1, -1, -2]
+envying	-0.8	1.32665	[-1, -1, -1, -1, -3, 2, -2, -1, 1, -1]
+envyingly	-1.3	1.55242	[-2, 3, -2, -2, -1, -3, -1, -1, -2, -2]
+erroneous	-1.8	0.6	[-2, -3, -2, -2, -2, -2, -1, -1, -1, -2]
+error	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -1, -2, -3, -2]
+errors	-1.4	0.66332	[-2, -1, -2, 0, -2, -2, -1, -1, -1, -2]
+escape	0.7	1.00499	[2, 0, 0, 1, 0, 1, 0, 3, 0, 0]
+escapes	0.5	1.36015	[4, 1, 1, 0, -1, 0, -1, 0, 1, 0]
+escaping	0.2	1.46969	[-2, 2, -1, 0, 1, 0, 2, 2, -2, 0]
+esteemed	1.9	0.83066	[3, 2, 1, 2, 3, 1, 1, 2, 3, 1]
+ethical	2.3	0.78102	[3, 3, 3, 3, 2, 2, 1, 3, 2, 1]
+euphoria	3.3	0.9	[4, 4, 3, 3, 3, 4, 4, 4, 1, 3]
+euphoric	3.2	0.87178	[3, 4, 3, 3, 3, 4, 4, 4, 1, 3]
+eviction	-2.0	0.63246	[-2, -2, -3, -2, -3, -2, -1, -2, -1, -2]
+evil	-3.4	0.91652	[-4, -4, -4, -3, -3, -4, -1, -4, -3, -4]
+evildoer	-3.1	0.7	[-2, -3, -3, -3, -4, -4, -3, -2, -3, -4]
+evildoers	-2.4	0.4899	[-3, -3, -2, -2, -2, -2, -2, -2, -3, -3]
+evildoing	-3.1	0.7	[-4, -4, -3, -3, -3, -4, -2, -3, -2, -3]
+evildoings	-2.5	1.0247	[-3, -1, -1, -3, -4, -2, -4, -2, -2, -3]
+eviler	-2.1	1.13578	[-2, -1, -3, -2, -4, -3, -1, -2, 0, -3]
+evilest	-2.5	1.0247	[-3, -4, -1, -3, -2, -3, -1, -4, -2, -2]
+eviller	-2.9	0.83066	[-3, -3, -4, -2, -2, -3, -2, -4, -2, -4]
+evillest	-3.3	0.78102	[-3, -4, -2, -3, -4, -2, -4, -4, -3, -4]
+evilly	-3.4	0.8	[-2, -4, -4, -4, -3, -4, -4, -4, -3, -2]
+evilness	-3.1	1.04403	[-3, -4, -4, -4, -4, -2, -3, -2, -1, -4]
+evils	-2.7	0.78102	[-3, -2, -2, -4, -4, -2, -3, -2, -3, -2]
+exaggerate	-0.6	0.66332	[-1, -1, -1, 0, -1, 0, 1, -1, -1, -1]
+exaggerated	-0.4	1.2	[-1, -1, -1, -1, -1, 2, 1, 1, -2, -1]
+exaggerates	-0.6	1.28062	[-1, -1, -1, -1, -1, 1, 0, 2, -3, -1]
+exaggerating	-0.7	0.9	[-1, -2, 0, -1, 0, 0, -2, -1, 1, -1]
+exasperated	-1.8	1.53623	[-4, -3, -3, -1, -1, -1, 1, -1, -4, -1]
+excel	2.0	1.0	[3, 0, 2, 3, 1, 1, 3, 3, 2, 2]
+excelled	2.2	0.87178	[1, 2, 2, 2, 3, 2, 4, 3, 2, 1]
+excellence	3.1	0.9434	[4, 3, 4, 3, 2, 3, 1, 4, 3, 4]
+excellences	2.5	0.92195	[4, 2, 2, 2, 4, 3, 2, 2, 3, 1]
+excellencies	2.4	0.4899	[3, 2, 3, 3, 2, 2, 2, 2, 3, 2]
+excellency	2.5	0.80623	[4, 2, 3, 3, 2, 3, 1, 3, 2, 2]
+excellent	2.7	0.64031	[2, 3, 3, 3, 3, 2, 3, 2, 2, 4]
+excellently	3.1	0.7	[4, 3, 3, 3, 2, 3, 3, 4, 4, 2]
+excelling	2.5	0.67082	[2, 2, 3, 3, 3, 2, 2, 4, 2, 2]
+excels	2.5	0.92195	[4, 2, 4, 2, 2, 1, 2, 3, 3, 2]
+excelsior	0.7	0.64031	[1, 0, 0, 2, 0, 1, 1, 1, 1, 0]
+excitabilities	1.5	1.0247	[2, 0, 1, 1, 3, 1, 2, 3, 2, 0]
+excitability	1.2	0.87178	[0, 1, 1, 0, 1, 2, 3, 1, 2, 1]
+excitable	1.5	0.92195	[2, 3, 1, 0, 1, 2, 2, 0, 2, 2]
+excitableness	1.0	1.09545	[0, 0, 2, 0, 2, 0, 2, 0, 1, 3]
+excitant	1.8	1.16619	[1, 0, 1, 3, 2, 0, 3, 3, 2, 3]
+excitants	1.2	0.9798	[1, 0, 1, 2, 2, 2, 1, -1, 2, 2]
+excitation	1.8	0.87178	[2, 0, 3, 1, 3, 2, 2, 2, 1, 2]
+excitations	1.8	1.16619	[3, 3, -1, 2, 2, 2, 1, 1, 3, 2]
+excitative	0.3	0.78102	[0, 1, 1, 0, 0, 0, 2, 0, -1, 0]
+excitatory	1.1	1.7	[-1, 2, 2, 1, 2, 2, 2, 3, -3, 1]
+excite	2.1	1.22066	[1, 2, 2, 1, 2, 0, 4, 4, 3, 2]
+excited	1.4	0.4899	[1, 1, 2, 1, 2, 1, 2, 1, 1, 2]
+excitedly	2.3	0.9	[3, 3, 2, 3, 1, 3, 1, 3, 1, 3]
+excitement	2.2	0.4	[2, 2, 2, 3, 3, 2, 2, 2, 2, 2]
+excitements	1.9	0.53852	[2, 1, 2, 3, 2, 2, 2, 2, 2, 1]
+exciter	1.9	0.9434	[3, 2, 3, 1, 0, 1, 2, 3, 2, 2]
+exciters	1.4	1.42829	[1, 2, 0, 1, 2, 4, 0, -1, 3, 2]
+excites	2.1	0.83066	[2, 3, 3, 2, 0, 2, 2, 3, 2, 2]
+exciting	2.2	0.87178	[3, 2, 1, 1, 1, 3, 3, 3, 2, 3]
+excitingly	1.9	0.9434	[3, 2, 3, 0, 1, 2, 1, 2, 2, 3]
+exciton	0.3	0.64031	[2, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+excitonic	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
+excitons	0.8	0.6	[1, 2, 0, 1, 1, 0, 0, 1, 1, 1]
+excitor	0.5	0.67082	[2, 0, 0, 0, 1, 1, 1, 0, 0, 0]
+exclude	-0.9	1.13578	[-1, -2, -1, -3, -1, 1, -1, -1, 1, -1]
+excluded	-1.4	1.62481	[-2, -1, -3, -3, -2, -3, -2, 1, -1, 2]
+exclusion	-1.2	1.249	[-2, -2, -3, -1, -2, -1, -1, -1, 2, -1]
+exclusive	0.5	0.92195	[0, 0, 0, -1, 2, 0, 1, 2, 1, 0]
+excruciate	-2.7	0.64031	[-2, -3, -2, -3, -3, -2, -4, -3, -2, -3]
+excruciated	-1.3	1.9	[-4, -1, -4, 0, 2, -2, -1, -1, -3, 1]
+excruciates	-1.0	2.19089	[-4, 1, -4, 0, 1, -3, -1, 1, -3, 2]
+excruciating	-3.3	0.9	[-3, -4, -4, -4, -4, -4, -4, -2, -2, -2]
+excruciatingly	-2.9	1.04403	[-2, -4, -3, -2, -4, -1, -2, -3, -4, -4]
+excruciation	-3.4	0.66332	[-4, -3, -2, -4, -4, -3, -4, -3, -3, -4]
+excruciations	-1.9	1.51327	[-3, -3, -2, -4, -1, -1, 1, -4, -1, -1]
+excuse	0.3	1.73494	[0, 0, 3, -1, 0, -1, -2, 0, 4, 0]
+exempt	0.4	0.91652	[1, 0, 0, 0, 2, -1, 0, 0, 2, 0]
+exhaust	-1.2	0.87178	[0, -1, 0, -1, -1, -3, -2, -2, -1, -1]
+exhausted	-1.5	1.28452	[-2, -1, 2, -2, -3, -2, -2, -1, -2, -2]
+exhauster	-1.3	0.64031	[-1, -1, 0, -1, -2, -1, -1, -2, -2, -2]
+exhausters	-1.3	0.45826	[-2, -1, -2, -1, -1, -2, -1, -1, -1, -1]
+exhaustibility	-0.8	1.07703	[0, -2, -3, 0, 1, -1, -1, -1, 0, -1]
+exhaustible	-1.0	0.63246	[-1, -1, 0, -1, -2, -2, -1, 0, -1, -1]
+exhausting	-1.5	0.5	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -2]
+exhaustion	-1.5	0.92195	[-2, -1, 1, -2, -2, -2, -2, -1, -2, -2]
+exhaustions	-1.1	0.9434	[-1, -3, -2, -1, -1, -1, -1, 1, -1, -1]
+exhaustive	-0.5	0.67082	[-1, -1, 0, -1, -2, 0, 0, 0, 0, 0]
+exhaustively	-0.7	0.78102	[-2, 0, -1, -1, -1, -2, 0, 0, 0, 0]
+exhaustiveness	-1.1	1.3	[-2, -2, 0, -1, -1, 1, -4, -1, 0, -1]
+exhaustless	0.2	1.8868	[1, 1, 0, 2, 3, 0, -2, 2, -2, -3]
+exhaustlessness	0.9	1.75784	[2, 2, 1, 1, -4, 2, 1, 2, 0, 2]
+exhausts	-1.1	0.53852	[-2, -1, 0, -1, -1, -2, -1, -1, -1, -1]
+exhilarated	3.0	0.63246	[3, 3, 3, 3, 2, 2, 4, 4, 3, 3]
+exhilarates	2.8	1.07703	[4, 3, 3, 3, 0, 2, 3, 4, 3, 3]
+exhilarating	1.7	1.61555	[3, 4, 3, 2, -1, 1, 1, 3, -1, 2]
+exonerate	1.8	0.74833	[2, 2, 2, 2, 3, 2, 1, 0, 2, 2]
+exonerated	1.8	1.83303	[3, -2, 2, 3, 2, 4, 3, 1, -1, 3]
+exonerates	1.6	1.90788	[3, -2, 1, 2, 3, 4, 0, 3, -1, 3]
+exonerating	1.0	1.41421	[2, -2, 3, 0, 0, 2, 0, 2, 2, 1]
+expand	1.3	0.64031	[0, 2, 2, 1, 1, 1, 2, 1, 2, 1]
+expands	0.4	0.66332	[0, 1, 0, 0, 0, 0, 0, 0, 2, 1]
+expel	-1.9	1.44568	[0, -4, -3, -1, -3, -1, 0, -2, -4, -1]
+expelled	-1.0	1.94936	[-1, -2, 2, -2, -4, -3, -2, 1, 2, -1]
+expelling	-1.6	1.49666	[-2, -2, -2, -2, -2, -3, -4, -1, 1, 1]
+expels	-1.6	1.11355	[-4, -2, 0, -3, -1, -1, -1, -2, -1, -1]
+exploit	-0.4	1.62481	[-2, -1, -1, 2, -2, -2, 2, -1, 2, -1]
+exploited	-2.0	1.0	[-3, -3, -1, -1, -1, -4, -2, -2, -1, -2]
+exploiting	-1.9	1.22066	[0, -3, -3, 0, -2, -3, -1, -1, -3, -3]
+exploits	-1.4	0.8	[-2, -2, -2, -1, -1, 0, -2, 0, -2, -2]
+exploration	0.9	0.7	[2, 2, 0, 1, 1, 0, 1, 0, 1, 1]
+explorations	0.3	1.1	[1, 1, 0, 0, 1, 2, 1, -2, -1, 0]
+expose	-0.6	0.8	[-1, -1, 0, 0, -2, 1, -1, 0, -1, -1]
+exposed	-0.3	1.18743	[-2, -1, 0, 2, 0, 0, -1, 1, -2, 0]
+exposes	-0.5	0.92195	[-1, -1, 0, 2, -1, 0, -1, -1, -1, -1]
+exposing	-1.1	0.7	[-2, -2, -1, -1, 0, -2, -1, -1, 0, -1]
+extend	0.7	0.78102	[2, 0, 0, 0, 1, 2, 1, 1, 0, 0]
+extends	0.5	0.80623	[2, 0, 2, 0, 0, 0, 1, 0, 0, 0]
+exuberant	2.8	0.6	[2, 3, 2, 3, 2, 4, 3, 3, 3, 3]
+exultant	3.0	1.18322	[4, 4, 3, 0, 3, 4, 3, 3, 2, 4]
+exultantly	1.4	1.49666	[3, 2, 4, 1, 1, 2, -2, 1, 1, 1]
+fab	2.0	1.0	[2, 1, 1, 3, 1, 2, 2, 4, 3, 1]
+fabulous	2.4	0.8	[2, 2, 3, 4, 3, 3, 1, 2, 2, 2]
+fabulousness	2.8	1.07703	[4, 1, 4, 3, 1, 3, 3, 2, 4, 3]
+fad	0.9	0.83066	[2, 0, 1, 1, 1, 0, 0, 2, 2, 0]
+fag	-2.1	0.83066	[-3, -1, -2, -4, -2, -2, -2, -1, -2, -2]
+faggot	-3.4	0.8	[-2, -4, -4, -3, -2, -4, -4, -4, -3, -4]
+faggots	-3.2	0.9798	[-2, -4, -4, -4, -3, -4, -4, -3, -1, -3]
+fail	-2.5	0.67082	[-2, -3, -3, -3, -4, -2, -2, -2, -2, -2]
+failed	-2.3	0.9	[-2, -3, -1, -2, -2, -1, -3, -3, -4, -2]
+failing	-2.3	1.1	[-2, -3, -3, -3, -4, -1, -2, -2, 0, -3]
+failingly	-1.4	0.8	[-1, -3, -2, -1, 0, -1, -2, -1, -2, -1]
+failings	-2.2	1.07703	[-2, -2, -3, -4, -1, -2, -1, -1, -4, -2]
+faille	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+fails	-1.8	0.74833	[-2, -3, -2, -3, -2, -2, -1, -1, -1, -1]
+failure	-2.3	1.00499	[-3, -1, -3, -2, -1, -2, -3, -1, -4, -3]
+failures	-2.0	0.63246	[-1, -2, -1, -2, -3, -2, -2, -3, -2, -2]
+fainthearted	-0.3	1.34536	[3, -1, -1, -1, -2, -1, 0, 1, -1, 0]
+fair	1.3	1.00499	[0, 1, 1, 2, 4, 1, 1, 1, 1, 1]
+faith	1.8	0.6	[1, 3, 2, 2, 1, 2, 2, 2, 1, 2]
+faithed	1.3	1.00499	[3, 2, 1, 2, 1, 2, -1, 1, 1, 1]
+faithful	1.9	0.83066	[1, 3, 2, 2, 1, 1, 3, 3, 2, 1]
+faithfully	1.8	1.07703	[3, 1, 2, 2, 4, 1, 0, 1, 2, 2]
+faithfulness	1.9	0.53852	[1, 2, 2, 3, 2, 2, 2, 1, 2, 2]
+faithless	-1.0	0.89443	[-1, -1, -1, -2, -2, -1, -1, 0, 1, -2]
+faithlessly	-0.9	1.51327	[-1, -2, -1, -3, -2, -1, 3, 0, -1, -1]
+faithlessness	-1.8	1.249	[-3, -2, 1, -2, -2, -1, -2, -1, -4, -2]
+faiths	1.8	0.9798	[2, 3, 1, 1, 3, 3, 0, 2, 2, 1]
+fake	-2.1	0.9434	[-2, -2, -1, -1, -1, -3, -3, -4, -2, -2]
+fakes	-1.8	1.07703	[-2, -3, -2, -2, -3, 1, -2, -2, -1, -2]
+faking	-1.8	0.87178	[-3, -1, -2, -1, -2, -2, -3, -2, 0, -2]
+fallen	-1.5	0.80623	[-1, -1, -2, -2, -1, -3, 0, -1, -2, -2]
+falling	-0.6	1.8	[-2, -2, -1, 0, -1, 3, -3, 2, 0, -2]
+falsified	-1.6	0.91652	[-4, -1, -1, -2, -1, -1, -2, -2, -1, -1]
+falsify	-2.0	0.7746	[-2, -1, -3, -3, -1, -2, -2, -2, -1, -3]
+fame	1.9	1.13578	[0, 2, 1, 2, 2, 4, 1, 3, 3, 1]
+fan	1.3	0.78102	[2, 0, 1, 1, 2, 1, 1, 3, 1, 1]
+fantastic	2.6	0.91652	[1, 3, 3, 3, 2, 4, 4, 2, 2, 2]
+fantastical	2.0	1.18322	[-1, 3, 2, 2, 2, 2, 3, 1, 3, 3]
+fantasticalities	2.1	1.04403	[2, 4, 2, 2, 1, 1, 2, 4, 1, 2]
+fantasticality	1.7	1.26886	[4, 1, 0, 2, 2, 1, 4, 1, 1, 1]
+fantasticalness	1.3	1.9	[2, 3, -3, 0, 3, 2, 2, 3, -1, 2]
+fantasticate	1.5	1.96214	[1, 2, -3, 1, 4, 1, 3, 4, 0, 2]
+fantastico	0.4	1.49666	[0, 0, 2, 0, 2, -2, 1, -1, -1, 3]
+farce	-1.7	0.45826	[-2, -2, -1, -2, -2, -1, -1, -2, -2, -2]
+fascinate	2.4	1.0198	[4, 2, 2, 3, 1, 2, 3, 4, 1, 2]
+fascinated	2.1	0.83066	[2, 2, 2, 3, 1, 2, 4, 2, 1, 2]
+fascinates	2.0	0.44721	[2, 3, 1, 2, 2, 2, 2, 2, 2, 2]
+fascination	2.2	0.74833	[2, 1, 3, 3, 2, 3, 2, 2, 1, 3]
+fascinating	2.5	0.92195	[3, 3, 3, 4, 2, 3, 2, 3, 1, 1]
+fascist	-2.6	0.8	[-3, -3, -2, -2, -2, -3, -1, -3, -4, -3]
+fascists	-0.8	1.6	[-2, -3, -1, 1, -1, 2, -3, 1, -1, -1]
+fatal	-2.5	1.62788	[-2, -3, -3, -4, -3, -3, 2, -4, -2, -3]
+fatalism	-0.6	1.8	[0, 0, -3, -4, -1, 1, 0, 2, -2, 1]
+fatalisms	-1.7	0.9	[-2, -4, -2, -2, -2, -1, -1, -1, -1, -1]
+fatalist	-0.5	1.56525	[0, 0, -1, -4, -1, 2, 0, 1, -2, 0]
+fatalistic	-1.0	1.34164	[-3, -1, -3, -1, 1, 0, 1, -2, -1, -1]
+fatalists	-1.2	0.87178	[0, -2, -1, -2, -1, 0, -1, -1, -3, -1]
+fatalities	-2.9	0.7	[-2, -3, -3, -4, -2, -2, -3, -4, -3, -3]
+fatality	-3.5	0.67082	[-2, -4, -4, -4, -3, -4, -4, -4, -3, -3]
+fatally	-3.2	0.74833	[-3, -2, -4, -2, -3, -4, -4, -3, -3, -4]
+fatigue	-1.0	0.7746	[-2, -1, -1, -1, 1, -1, -2, -1, -1, -1]
+fatigued	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -1]
+fatigues	-1.3	1.00499	[-2, -1, -1, -2, -1, 1, -3, -2, -1, -1]
+fatiguing	-1.2	0.6	[-1, -2, -2, -1, 0, -2, -1, -1, -1, -1]
+fatiguingly	-1.5	0.80623	[-1, 0, -3, -2, -1, -1, -2, -1, -2, -2]
+fault	-1.7	0.64031	[-1, -2, -2, -2, -1, -1, -2, -2, -1, -3]
+faulted	-1.4	0.4899	[-2, -2, -1, -2, -1, -1, -1, -1, -2, -1]
+faultfinder	-0.8	1.32665	[-3, -2, -2, -1, 1, 1, 1, -1, -1, -1]
+faultfinders	-1.5	0.80623	[-2, -2, -1, -3, -2, -1, 0, -1, -1, -2]
+faultfinding	-2.1	0.83066	[-3, -2, -1, -2, -1, -3, -1, -3, -2, -3]
+faultier	-2.1	0.7	[-3, -3, -3, -1, -2, -2, -2, -1, -2, -2]
+faultiest	-2.1	0.53852	[-3, -1, -2, -2, -2, -2, -2, -2, -3, -2]
+faultily	-2.0	0.89443	[-2, -2, -2, -3, -2, -1, 0, -3, -2, -3]
+faultiness	-1.5	0.92195	[-1, -1, -3, -1, 0, -2, -3, -1, -2, -1]
+faulting	-1.4	0.4899	[-1, -2, -1, -1, -2, -1, -1, -2, -1, -2]
+faultless	2.0	1.41421	[3, 2, 0, 1, 3, 1, 4, 0, 2, 4]
+faultlessly	2.0	1.09545	[3, 3, 2, 2, 0, 3, 2, 3, 2, 0]
+faultlessness	1.1	2.02237	[3, 2, 4, 2, 1, -1, -2, 1, -2, 3]
+faults	-2.1	0.3	[-2, -2, -2, -2, -2, -2, -3, -2, -2, -2]
+faulty	-1.3	0.45826	[-1, -1, -1, -1, -2, -2, -2, -1, -1, -1]
+fav	2.0	0.63246	[2, 1, 2, 2, 2, 1, 3, 2, 3, 2]
+fave	1.9	1.51327	[1, 3, -2, 3, 2, 3, 1, 3, 2, 3]
+favor	1.7	0.64031	[2, 2, 2, 2, 2, 2, 0, 1, 2, 2]
+favorable	2.1	0.7	[2, 1, 2, 3, 1, 2, 2, 3, 3, 2]
+favorableness	2.2	0.87178	[1, 2, 1, 3, 2, 2, 2, 4, 2, 3]
+favorably	1.6	0.66332	[2, 1, 1, 1, 1, 2, 2, 2, 3, 1]
+favored	1.8	0.6	[2, 2, 1, 1, 3, 1, 2, 2, 2, 2]
+favorer	1.3	1.18743	[2, 2, 1, 1, -2, 1, 2, 2, 2, 2]
+favorers	1.4	0.4899	[2, 2, 1, 2, 1, 2, 1, 1, 1, 1]
+favoring	1.8	0.6	[2, 1, 1, 3, 2, 2, 1, 2, 2, 2]
+favorite	2.0	0.63246	[2, 1, 3, 1, 2, 2, 2, 3, 2, 2]
+favorited	1.7	0.45826	[1, 2, 2, 1, 2, 2, 2, 1, 2, 2]
+favorites	1.8	0.6	[1, 2, 1, 3, 2, 2, 1, 2, 2, 2]
+favoritism	0.7	1.79165	[-1, 3, -1, -1, 2, -2, 2, 2, 3, 0]
+favoritisms	0.7	0.9	[0, 2, -1, 1, 0, 0, 1, 1, 2, 1]
+favors	1.0	0.7746	[2, 1, 1, 1, 2, 1, -1, 1, 1, 1]
+favour	1.9	0.53852	[2, 1, 2, 3, 2, 2, 2, 1, 2, 2]
+favoured	1.8	0.4	[1, 2, 2, 2, 1, 2, 2, 2, 2, 2]
+favourer	1.6	0.4899	[1, 2, 2, 1, 1, 2, 2, 2, 1, 2]
+favourers	1.6	0.66332	[2, 2, 1, 0, 2, 2, 1, 2, 2, 2]
+favouring	1.3	0.45826	[1, 2, 1, 1, 2, 1, 1, 1, 1, 2]
+favours	1.8	0.6	[3, 2, 1, 2, 1, 2, 2, 1, 2, 2]
+fear	-2.2	0.6	[-2, -3, -2, -3, -2, -1, -2, -3, -2, -2]
+feared	-2.2	0.6	[-2, -3, -2, -1, -3, -2, -3, -2, -2, -2]
+fearful	-2.2	0.87178	[-2, -2, -3, -1, -2, -3, -2, -2, -4, -1]
+fearfuller	-2.2	0.87178	[-1, -4, -2, -2, -1, -2, -3, -2, -3, -2]
+fearfullest	-2.5	1.0247	[-3, -3, -4, -4, -3, -2, -1, -2, -2, -1]
+fearfully	-2.2	0.87178	[-2, -2, -2, -1, -1, -3, -4, -2, -3, -2]
+fearfulness	-1.8	0.87178	[-1, -1, -1, -2, -2, -1, -4, -2, -2, -2]
+fearing	-2.7	0.9	[-3, -3, -3, -2, -4, -2, -1, -3, -2, -4]
+fearless	1.9	0.83066	[3, 3, 3, 2, 2, 2, 1, 1, 1, 1]
+fearlessly	1.1	1.22066	[2, -2, 1, 1, 2, 1, 3, 1, 1, 1]
+fearlessness	1.1	1.13578	[3, 2, -1, 2, 0, 2, 1, 1, 1, 0]
+fears	-1.8	0.6	[-2, -2, -3, -2, -2, -1, -1, -2, -1, -2]
+fearsome	-1.7	0.64031	[-3, -1, -1, -2, -1, -2, -2, -2, -1, -2]
+fed up	-1.8	1.249	[-2, -2, -3, -4, -2, -2, -1, -2, -1, 1]
+feeble	-1.2	1.249	[-2, -2, -3, -1, -1, -2, -1, -1, 2, -1]
+feeling	0.5	1.0247	[0, 0, 0, 3, 0, 2, 0, 0, 0, 0]
+felonies	-2.5	0.5	[-3, -3, -3, -2, -2, -2, -2, -3, -2, -3]
+felony	-2.5	1.36015	[-4, -3, -4, -2, -3, -3, -2, -3, -2, 1]
+ferocious	-0.4	1.56205	[1, 1, -2, -3, -1, 2, 1, -2, -1, 0]
+ferociously	-1.1	1.86815	[-3, -4, 2, -2, 0, -2, -1, -1, 2, -2]
+ferociousness	-1.0	1.89737	[2, -4, -2, 0, -2, -3, -1, 0, 2, -2]
+ferocities	-1.0	1.54919	[1, 0, -2, 0, 0, -3, 0, 0, -2, -4]
+ferocity	-0.7	1.67631	[-2, -1, -4, 0, 0, -3, 1, 1, 0, 1]
+fervent	1.1	1.44568	[3, 0, 0, 1, -2, 2, 2, 3, 1, 1]
+fervid	0.5	2.20227	[4, -2, 1, -2, 4, 0, -1, 2, 1, -2]
+festival	2.2	0.6	[2, 2, 3, 2, 3, 2, 2, 2, 3, 1]
+festivalgoer	1.3	1.1	[1, 3, 2, 3, 0, 0, 1, 2, 0, 1]
+festivalgoers	1.2	0.9798	[2, 2, 0, 0, 0, 2, 2, 0, 2, 2]
+festivals	1.5	1.11803	[2, 0, 2, 3, 0, 3, 2, 1, 2, 0]
+festive	2.0	0.63246	[2, 3, 2, 3, 1, 2, 2, 2, 1, 2]
+festively	2.2	0.6	[2, 2, 3, 1, 3, 2, 3, 2, 2, 2]
+festiveness	2.4	0.8	[1, 3, 2, 1, 3, 3, 3, 3, 2, 3]
+festivities	2.1	0.7	[1, 2, 1, 2, 3, 2, 3, 3, 2, 2]
+festivity	2.2	1.07703	[3, 3, 3, 0, 2, 1, 3, 3, 1, 3]
+feud	-1.4	0.66332	[-3, -2, -1, -2, -1, -1, -1, -1, -1, -1]
+feudal	-0.8	0.87178	[-1, -2, -2, 0, 0, 0, -2, -1, 0, 0]
+feudalism	-0.9	1.37477	[-2, -3, -2, -3, 0, 0, 1, 0, 0, 0]
+feudalisms	-0.2	0.74833	[0, 0, 0, 0, 0, 0, -1, 0, -2, 1]
+feudalist	-0.9	1.13578	[-2, -2, -2, -2, 0, 0, 1, 0, 0, -2]
+feudalistic	-1.1	0.7	[0, -1, -1, 0, -2, -1, -2, -1, -2, -1]
+feudalities	-0.4	1.0198	[-1, 0, -1, -2, -1, 0, -1, 0, 0, 2]
+feudality	-0.5	1.28452	[1, -1, 0, -1, 1, 0, -3, -2, 1, -1]
+feudalization	-0.3	1.18743	[-2, -2, 0, 0, 2, 0, -1, -1, 1, 0]
+feudalize	-0.5	0.92195	[-1, 0, -1, 0, -2, 0, 1, 0, 0, -2]
+feudalized	-0.8	1.07703	[-1, -1, -3, 0, 0, 0, 1, -1, -2, -1]
+feudalizes	-0.1	0.53852	[0, 0, -1, 0, -1, 0, 0, 0, 1, 0]
+feudalizing	-0.7	1.34536	[2, -2, -1, 0, 0, -2, -1, -2, 1, -2]
+feudally	-0.6	0.66332	[0, 0, -1, -1, 0, -1, 0, -1, -2, 0]
+feudaries	-0.3	0.9	[0, 0, 0, -2, -2, 0, 0, 0, 0, 1]
+feudary	-0.8	0.74833	[0, 0, -1, -1, -2, 0, -1, 0, -2, -1]
+feudatories	-0.5	0.92195	[-3, 0, -1, 0, 0, 0, 0, -1, 0, 0]
+feudatory	-0.1	0.83066	[-2, 0, 0, 0, 1, 0, 1, -1, 0, 0]
+feuded	-2.2	0.6	[-2, -2, -2, -1, -3, -3, -2, -3, -2, -2]
+feuding	-1.6	0.66332	[-2, -1, -2, -2, -1, -1, -3, -1, -2, -1]
+feudist	-1.1	0.83066	[-2, 0, -3, -1, -1, -1, 0, -1, -1, -1]
+feudists	-0.7	0.9	[0, 0, -1, 0, 0, -2, -2, 0, -2, 0]
+feuds	-1.4	1.0198	[-2, -2, -2, -1, -1, -1, -3, -2, 1, -1]
+fiasco	-2.3	0.64031	[-2, -2, -3, -3, -2, -3, -1, -3, -2, -2]
+fidgety	-1.4	0.66332	[-1, -2, -2, 0, -1, -1, -2, -1, -2, -2]
+fiery	-1.4	0.91652	[0, -1, -1, -2, -2, 0, -3, -1, -2, -2]
+fiesta	2.1	0.7	[3, 2, 1, 2, 2, 1, 3, 3, 2, 2]
+fiestas	1.5	1.0247	[3, 0, 3, 1, 0, 2, 2, 1, 2, 1]
+fight	-1.6	1.56205	[-1, -2, -3, -3, -1, 2, -4, -1, -2, -1]
+fighter	0.6	1.11355	[3, 0, 0, -1, 1, 0, 1, 0, 2, 0]
+fighters	-0.2	1.46969	[-1, 2, -2, 0, 2, 0, -2, -2, 0, 1]
+fighting	-1.5	1.11803	[-1, -2, -3, -2, -2, -2, 0, -3, 0, 0]
+fightings	-1.9	0.53852	[-2, -3, -1, -2, -2, -2, -2, -1, -2, -2]
+fights	-1.7	0.64031	[-2, -2, -1, -2, -2, -1, -3, -1, -1, -2]
+fine	0.8	0.6	[1, 0, 1, 2, 1, 1, 1, 1, 0, 0]
+fire	-1.4	1.49666	[-2, 0, -4, 0, -2, -1, -1, 0, -4, 0]
+fired	-2.6	0.91652	[-2, -3, -4, -3, -3, -1, -3, -3, -1, -3]
+firing	-1.4	0.8	[0, -1, -1, -1, -1, -2, -2, -3, -2, -1]
+fit	1.5	1.0247	[2, 1, 2, 0, 4, 2, 1, 1, 1, 1]
+fitness	1.1	0.9434	[0, 2, 1, 0, 1, 3, 2, 1, 0, 1]
+flagship	0.4	0.91652	[0, 0, 0, 0, 0, 0, 0, 1, 3, 0]
+flatter	0.4	1.42829	[-2, -2, 1, 2, 1, -1, 1, 2, 1, 1]
+flattered	1.6	2.00998	[2, 3, 3, 1, 2, 3, 3, 1, 2, -4]
+flatterer	-0.3	1.9	[-4, 2, -1, 1, 2, 2, -2, -1, -1, -1]
+flatterers	0.3	1.84662	[2, 1, -2, 1, 0, -4, 2, 1, 2, 0]
+flatteries	1.2	1.16619	[2, 2, 3, 1, -1, 0, 0, 1, 2, 2]
+flattering	1.3	2.19317	[3, 2, 2, 3, -4, 4, -1, 2, 1, 1]
+flatteringly	1.0	1.61245	[2, 2, 1, 2, 1, -3, -1, 2, 2, 2]
+flatters	0.6	2.10713	[1, 1, 2, 2, 3, -1, -2, 2, -4, 2]
+flattery	0.4	1.49666	[1, -1, -2, 1, 3, -2, 1, 1, 1, 1]
+flawless	2.3	2.14709	[4, 3, 4, 4, 1, 2, 4, 4, -2, -1]
+flawlessly	0.8	1.83303	[-2, 2, 3, 1, 0, -2, 2, 2, -1, 3]
+flees	-0.7	1.18743	[-3, 0, -2, 0, -1, -1, -1, 1, -1, 1]
+flexibilities	1.0	1.09545	[1, 3, 1, 0, 1, -1, 2, 0, 2, 1]
+flexibility	1.4	0.8	[2, 2, 0, 2, 1, 2, 1, 0, 2, 2]
+flexible	0.9	0.83066	[2, 1, 0, 0, 1, 2, 0, 1, 2, 0]
+flexibly	1.3	0.78102	[2, 1, 0, 0, 1, 2, 2, 1, 2, 2]
+flirtation	1.7	0.64031	[3, 1, 1, 2, 2, 1, 2, 1, 2, 2]
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+freezingly	-1.6	0.4899	[-1, -2, -2, -1, -2, -2, -2, -2, -1, -1]
+frenzy	-1.3	1.48661	[-1, -1, -2, -2, 2, -4, -1, -2, 0, -2]
+fresh	1.3	0.45826	[2, 2, 1, 1, 1, 1, 2, 1, 1, 1]
+friend	2.2	0.6	[2, 2, 3, 2, 3, 3, 1, 2, 2, 2]
+friended	1.7	0.78102	[2, 2, 1, 3, 1, 1, 2, 3, 1, 1]
+friending	1.8	1.07703	[1, 4, 2, 0, 1, 3, 2, 2, 1, 2]
+friendless	-1.5	0.67082	[-1, -2, -2, -1, 0, -2, -1, -2, -2, -2]
+friendlessness	-0.3	2.05183	[-2, -2, 2, 1, -4, -1, 2, 1, -2, 2]
+friendlier	2.0	0.63246	[3, 2, 2, 1, 2, 2, 2, 1, 3, 2]
+friendlies	2.2	0.74833	[3, 2, 2, 3, 2, 2, 1, 3, 1, 3]
+friendliest	2.6	0.91652	[3, 3, 1, 3, 2, 1, 3, 3, 4, 3]
+friendlily	1.8	0.74833	[1, 2, 2, 1, 3, 1, 1, 2, 3, 2]
+friendliness	2.0	0.7746	[3, 1, 3, 2, 2, 3, 2, 1, 2, 1]
+friendly	2.2	0.6	[2, 1, 3, 3, 2, 2, 3, 2, 2, 2]
+friends	2.1	0.53852	[3, 3, 2, 2, 2, 1, 2, 2, 2, 2]
+friendship	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
+friendships	1.6	0.91652	[2, 1, 1, 0, 3, 2, 2, 3, 1, 1]
+fright	-1.6	1.35647	[-2, -1, 0, -3, -2, -4, 1, -1, -2, -2]
+frighted	-1.4	0.91652	[0, -1, -1, -1, -2, -1, -3, -1, -1, -3]
+frighten	-1.4	0.8	[0, -1, -1, -1, -2, -1, -3, -2, -1, -2]
+frightened	-1.9	0.7	[-2, -3, -1, -1, -2, -2, -3, -1, -2, -2]
+frightening	-2.2	0.9798	[-1, -1, -4, -3, -3, -3, -2, -2, -1, -2]
+frighteningly	-2.1	0.7	[-2, -2, -2, -2, -4, -2, -1, -2, -2, -2]
+frightens	-1.7	0.78102	[-2, -1, -2, -1, -1, -1, -2, -3, -3, -1]
+frightful	-2.3	0.78102	[-2, -2, -2, -2, -3, -2, -3, -1, -4, -2]
+frightfully	-1.7	0.78102	[-1, -1, -1, -2, -2, -1, -2, -3, -1, -3]
+frightfulness	-1.9	0.7	[-1, -1, -2, -3, -3, -2, -1, -2, -2, -2]
+frighting	-1.5	0.67082	[-1, -2, -2, -3, -1, -1, -1, -1, -2, -1]
+frights	-1.1	0.83066	[-2, 0, -2, 0, -2, -1, 0, -1, -1, -2]
+frisky	1.0	1.48324	[1, -2, 1, 1, 1, 3, 3, 2, -1, 1]
+frowning	-1.4	1.42829	[-1, -1, -1, -3, -3, 1, -2, -3, 1, -2]
+frustrate	-2.0	0.63246	[-2, -3, -2, -1, -3, -2, -2, -1, -2, -2]
+frustrated	-2.4	0.66332	[-2, -1, -3, -3, -2, -2, -3, -2, -3, -3]
+frustrates	-1.9	0.7	[-1, -1, -3, -2, -1, -2, -2, -2, -3, -2]
+frustrating	-1.9	0.83066	[-2, -2, -1, -1, -1, -2, -2, -2, -4, -2]
+frustratingly	-2.0	0.63246	[-1, -3, -2, -2, -2, -2, -2, -3, -2, -1]
+frustration	-2.1	0.7	[-3, -2, -3, -2, -1, -2, -3, -2, -1, -2]
+frustrations	-2.0	0.7746	[-2, -1, -1, -3, -2, -2, -3, -3, -2, -1]
+fuck	-2.5	1.20416	[0, -3, -4, -3, -2, -3, -4, -1, -2, -3]
+fucked	-3.4	0.66332	[-2, -3, -4, -3, -4, -4, -3, -4, -3, -4]
+fucker	-3.3	0.78102	[-3, -4, -4, -2, -3, -4, -4, -2, -4, -3]
+fuckers	-2.9	0.9434	[-3, -3, -4, -3, -4, -4, -2, -1, -2, -3]
+fuckface	-3.2	1.07703	[-4, -2, -4, -1, -4, -4, -2, -4, -3, -4]
+fuckhead	-3.1	1.04403	[-1, -4, -2, -4, -3, -3, -2, -4, -4, -4]
+fucks	-2.1	1.13578	[-3, -2, -1, -1, -1, -2, -4, -2, -4, -1]
+fucktard	-3.1	0.9434	[-4, -4, -4, -3, -4, -2, -4, -2, -2, -2]
+fud	-1.1	1.37477	[-1, -3, -1, -1, -3, -2, 2, 0, -1, -1]
+fuked	-2.5	0.92195	[-2, -3, -3, -3, -3, -3, 0, -3, -3, -2]
+fuking	-3.2	0.9798	[-4, -1, -3, -4, -3, -2, -4, -3, -4, -4]
+fulfill	1.9	1.04403	[1, 1, 2, 4, 1, 1, 2, 1, 3, 3]
+fulfilled	1.8	0.87178	[1, 2, 1, 0, 2, 2, 3, 2, 2, 3]
+fulfills	1.0	1.09545	[2, 1, 1, 1, 1, -2, 2, 2, 1, 1]
+fume	-1.2	1.16619	[0, 0, 0, -2, -3, -2, -1, -3, -1, 0]
+fumed	-1.8	0.87178	[-3, -2, -3, -2, -2, 0, -2, -1, -1, -2]
+fumeless	0.3	0.64031	[0, 0, 0, 1, 0, 0, 0, 2, 0, 0]
+fumelike	-0.7	1.18743	[0, 0, -3, 0, 0, -2, -1, -2, 1, 0]
+fumer	0.7	0.9	[2, 1, 0, 1, 0, 2, 0, -1, 1, 1]
+fumers	-0.8	0.6	[0, -1, -1, -2, -1, 0, 0, -1, -1, -1]
+fumes	-0.1	1.13578	[0, -2, 0, 0, -1, 1, -1, -1, 1, 2]
+fumet	0.4	1.0198	[2, 0, 0, -1, 0, 1, -1, 0, 2, 1]
+fumets	-0.4	0.66332	[0, -1, 0, -1, 0, 0, -2, 0, 0, 0]
+fumette	-0.6	1.11355	[-2, -2, 0, -1, -1, 2, 0, 0, -1, -1]
+fuming	-2.7	0.64031	[-2, -3, -3, -2, -3, -4, -3, -2, -2, -3]
+fun	2.3	0.45826	[2, 3, 2, 3, 2, 2, 3, 2, 2, 2]
+funeral	-1.5	1.74642	[-2, -3, -2, -1, -3, -1, -4, 1, 2, -2]
+funerals	-1.6	2.2891	[-3, -4, -1, -4, 2, -3, -3, 2, 1, -3]
+funky	-0.4	1.62481	[0, -1, 2, -1, 2, 0, -4, -1, 0, -1]
+funned	2.3	0.9	[2, 3, 3, 4, 1, 2, 2, 2, 3, 1]
+funnel	0.1	0.53852	[1, 0, 0, 0, 0, -1, 0, 0, 1, 0]
+funneled	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
+funnelform	0.5	0.80623	[0, 0, 1, 0, 0, 0, 0, 2, 2, 0]
+funneling	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+funnelled	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+funnelling	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+funnels	0.4	0.66332	[0, 0, 0, 1, 0, 0, 0, 0, 2, 1]
+funner	2.2	0.74833	[2, 2, 3, 4, 1, 2, 2, 2, 2, 2]
+funnest	2.9	0.7	[4, 3, 4, 3, 2, 3, 2, 3, 2, 3]
+funnier	1.7	1.00499	[2, 2, -1, 2, 2, 2, 3, 1, 2, 2]
+funnies	1.3	1.00499	[2, 1, -1, 2, 1, 2, 3, 1, 1, 1]
+funniest	2.6	0.8	[3, 3, 3, 3, 2, 2, 1, 2, 4, 3]
+funnily	1.9	0.53852	[2, 3, 1, 2, 2, 2, 2, 1, 2, 2]
+funniness	1.8	0.9798	[3, 2, 3, 2, 2, 1, 3, 0, 1, 1]
+funninesses	1.6	0.91652	[1, 3, 0, 3, 1, 2, 1, 2, 2, 1]
+funning	1.8	0.9798	[2, 2, 1, 2, 1, 4, 0, 2, 2, 2]
+funny	1.9	0.53852	[3, 2, 2, 1, 2, 2, 1, 2, 2, 2]
+funnyman	1.4	0.4899	[2, 2, 1, 2, 1, 1, 1, 1, 2, 1]
+funnymen	1.3	1.1	[2, 1, 1, 0, 0, 3, 3, 1, 2, 0]
+furious	-2.7	1.41774	[-3, -3, -3, -4, -4, -4, 1, -2, -3, -2]
+furiously	-1.9	1.04403	[-2, -2, -4, -2, -1, -2, -1, -3, 0, -2]
+fury	-2.7	0.78102	[-4, -3, -2, -2, -2, -3, -4, -2, -3, -2]
+futile	-1.9	0.83066	[0, -3, -2, -2, -2, -2, -3, -1, -2, -2]
+gag	-1.4	1.0198	[-2, -2, -1, -2, 0, -2, -3, 0, 0, -2]
+gagged	-1.3	1.55242	[-2, -2, -1, -2, 2, -3, -1, -3, 1, -2]
+gain	2.4	0.4899	[2, 3, 2, 2, 3, 2, 3, 2, 3, 2]
+gained	1.6	0.66332	[2, 1, 2, 1, 1, 3, 2, 1, 2, 1]
+gaining	1.8	0.4	[1, 2, 2, 2, 1, 2, 2, 2, 2, 2]
+gains	1.4	0.4899	[1, 2, 1, 2, 2, 2, 1, 1, 1, 1]
+gallant	1.7	1.1	[4, 0, 3, 1, 1, 2, 2, 2, 1, 1]
+gallantly	1.9	0.53852	[2, 2, 3, 2, 2, 2, 2, 1, 2, 1]
+gallantry	2.6	0.8	[3, 3, 1, 2, 2, 3, 4, 2, 3, 3]
+geek	-0.8	0.9798	[0, 0, 0, -2, -3, -1, -1, 0, 0, -1]
+geekier	0.2	1.4	[0, 3, -1, -1, -1, 1, 2, 1, -1, -1]
+geekiest	-0.1	0.9434	[1, -1, -1, -1, -1, 1, 1, 1, 0, -1]
+geeks	-0.4	0.91652	[0, 0, -1, 0, 0, 0, 0, 0, -3, 0]
+geeky	-0.6	0.91652	[0, 0, -1, 0, -1, 0, -1, 0, -3, 0]
+generosities	2.6	0.4899	[3, 3, 2, 3, 2, 3, 2, 3, 2, 3]
+generosity	2.3	0.64031	[3, 1, 2, 2, 3, 2, 3, 3, 2, 2]
+generous	2.3	0.78102	[3, 2, 4, 2, 2, 1, 2, 3, 2, 2]
+generously	1.8	0.74833	[3, 3, 2, 1, 2, 1, 1, 2, 1, 2]
+generousness	2.4	0.91652	[3, 2, 3, 1, 3, 4, 3, 2, 2, 1]
+genial	1.8	0.6	[3, 1, 2, 1, 2, 2, 1, 2, 2, 2]
+gentle	1.9	0.53852	[2, 2, 2, 1, 2, 3, 2, 2, 1, 2]
+gentler	1.4	0.4899	[2, 1, 1, 1, 1, 2, 2, 1, 2, 1]
+gentlest	1.8	0.4	[2, 1, 2, 2, 2, 1, 2, 2, 2, 2]
+gently	2.0	0.7746	[2, 2, 2, 1, 1, 3, 3, 2, 1, 3]
+ghost	-1.3	1.34536	[-2, 0, 0, 0, 0, -3, -2, -3, 0, -3]
+giddy	-0.6	1.62481	[-2, -2, 3, -1, -1, -1, -1, -2, 2, -1]
+gift	1.9	0.53852	[2, 1, 2, 2, 2, 1, 2, 3, 2, 2]
+giggle	1.8	0.9798	[2, 2, 2, 2, 2, 3, 2, -1, 2, 2]
+giggled	1.5	1.20416	[1, 3, 1, 3, 3, 1, 1, -1, 2, 1]
+giggler	0.6	0.8	[1, 1, 1, 1, -1, 1, 1, 1, -1, 1]
+gigglers	1.4	0.4899	[1, 2, 2, 1, 2, 1, 1, 1, 1, 2]
+giggles	0.8	1.249	[1, 2, 2, 1, -1, 1, 1, 2, -2, 1]
+gigglier	1.0	1.09545	[2, 1, 1, 2, 2, 1, -1, 2, 1, -1]
+giggliest	1.7	1.26886	[4, 2, 1, 2, 1, 3, 2, 2, -1, 1]
+giggling	1.5	0.5	[2, 2, 1, 2, 2, 1, 1, 1, 1, 2]
+gigglingly	1.1	1.37477	[1, 2, 1, 1, -1, 2, 1, -1, 4, 1]
+giggly	1.0	1.41421	[1, 2, -2, 1, 2, 3, 1, -1, 2, 1]
+giver	1.4	0.66332	[1, 2, 2, 0, 1, 2, 1, 2, 1, 2]
+givers	1.7	1.34536	[2, -1, 3, 3, 3, 1, 1, 2, 0, 3]
+giving	1.4	1.0198	[1, 1, 3, 1, 1, 2, 3, 0, 2, 0]
+glad	2.0	0.63246	[3, 2, 1, 2, 2, 2, 1, 3, 2, 2]
+gladly	1.4	0.4899	[2, 2, 1, 2, 1, 1, 2, 1, 1, 1]
+glamor	2.1	0.9434	[1, 2, 2, 2, 1, 3, 2, 4, 3, 1]
+glamorise	1.3	1.1	[0, 1, 4, 1, 0, 2, 1, 2, 1, 1]
+glamorised	1.8	0.74833	[1, 2, 2, 2, 2, 2, 0, 2, 3, 2]
+glamorises	2.1	1.04403	[1, 3, 2, 4, 2, 2, 0, 2, 3, 2]
+glamorising	1.2	1.16619	[3, 2, 0, 3, 1, 2, 0, 1, 0, 0]
+glamorization	1.6	0.91652	[2, 2, 3, 0, 3, 1, 2, 1, 1, 1]
+glamorize	1.7	1.1	[1, 2, 1, 4, 2, 0, 3, 1, 2, 1]
+glamorized	2.1	1.04403	[3, 2, 1, 2, 4, 2, 2, 0, 3, 2]
+glamorizer	2.4	1.0198	[3, 2, 2, 3, 4, 3, 2, 0, 3, 2]
+glamorizers	1.6	1.11355	[4, 1, 1, 1, 1, 2, 0, 2, 3, 1]
+glamorizes	2.4	1.2	[3, 2, 2, 4, 4, 1, 2, 0, 3, 3]
+glamorizing	1.8	1.16619	[3, 0, 1, 2, 3, 2, 1, 0, 3, 3]
+glamorous	2.3	0.78102	[3, 2, 4, 2, 2, 2, 3, 2, 2, 1]
+glamorously	2.1	1.04403	[1, 3, 2, 1, 2, 1, 4, 1, 3, 3]
+glamors	1.4	0.66332	[1, 1, 2, 2, 2, 1, 2, 2, 0, 1]
+glamour	2.4	0.91652	[2, 4, 2, 1, 3, 2, 2, 2, 2, 4]
+glamourize	0.8	1.32665	[2, 1, 0, 1, 0, 4, 0, 0, -1, 1]
+glamourless	-1.6	1.49666	[-4, -1, -1, -2, -2, -3, -2, -1, 2, -2]
+glamourous	2.0	0.7746	[1, 3, 3, 2, 1, 2, 2, 2, 3, 1]
+glamours	1.9	0.83066	[1, 3, 2, 2, 3, 2, 1, 1, 3, 1]
+glee	3.2	0.4	[3, 4, 3, 3, 4, 3, 3, 3, 3, 3]
+gleeful	2.9	0.53852	[3, 3, 3, 3, 3, 4, 2, 2, 3, 3]
+gloom	-2.6	0.66332	[-4, -2, -3, -3, -2, -3, -2, -2, -2, -3]
+gloomed	-1.9	0.7	[-1, -2, -3, -1, -2, -2, -1, -2, -3, -2]
+gloomful	-2.1	0.9434	[-3, -1, -4, -2, -1, -1, -2, -3, -2, -2]
+gloomier	-1.5	1.20416	[-3, -2, -2, -3, -1, -2, 0, 1, -1, -2]
+gloomiest	-1.8	2.03961	[-2, -2, 2, -4, -2, -3, -4, -3, 2, -2]
+gloominess	-1.8	0.6	[-2, -1, -2, -3, -2, -1, -2, -2, -2, -1]
+gloominesses	-1.0	1.09545	[-1, -2, -2, -1, -1, -2, 2, -1, -1, -1]
+glooming	-1.8	0.74833	[-1, -2, -2, -1, -2, -1, -3, -1, -3, -2]
+glooms	-0.9	1.57797	[3, -2, -1, -2, -2, -2, 1, -2, -1, -1]
+gloomy	-0.6	1.56205	[2, -1, -2, -2, -2, -1, 1, -2, 2, -1]
+gloried	2.4	1.0198	[2, 3, 3, 4, 4, 1, 1, 2, 2, 2]
+glories	2.1	1.3	[4, 1, 4, 1, 1, 4, 2, 2, 1, 1]
+glorification	2.0	0.89443	[3, 1, 3, 2, 3, 1, 1, 3, 2, 1]
+glorified	2.3	0.9	[1, 4, 2, 2, 4, 2, 2, 2, 2, 2]
+glorifier	2.3	1.00499	[1, 4, 1, 2, 4, 2, 3, 2, 2, 2]
+glorifiers	1.6	1.0198	[2, 1, 2, -1, 2, 2, 2, 1, 2, 3]
+glorifies	2.2	0.9798	[1, 4, 2, 2, 4, 2, 1, 2, 2, 2]
+glorify	2.7	0.78102	[3, 3, 4, 3, 1, 3, 2, 3, 2, 3]
+glorifying	2.4	1.28062	[3, 4, 2, 2, 4, 4, 0, 1, 2, 2]
+gloriole	1.5	1.36015	[2, 4, 1, 2, 0, -1, 1, 3, 2, 1]
+glorioles	1.2	0.87178	[0, 2, 0, 2, 0, 1, 2, 2, 1, 2]
+glorious	3.2	0.6	[4, 3, 3, 2, 3, 3, 3, 4, 3, 4]
+gloriously	2.9	0.83066	[3, 4, 3, 2, 4, 2, 2, 2, 4, 3]
+gloriousness	2.6	1.0198	[3, 2, 3, 4, 3, 2, 1, 4, 3, 1]
+glory	2.5	0.80623	[1, 3, 3, 1, 3, 3, 3, 2, 3, 3]
+glum	-2.1	0.7	[-2, -1, -3, -3, -1, -2, -2, -3, -2, -2]
+gn8	0.6	0.66332	[1, 1, 0, 0, 0, 0, 2, 1, 0, 1]
+god	1.1	1.51327	[0, 0, 0, 1, 0, 3, 0, 3, 0, 4]
+goddam	-2.5	1.28452	[0, -3, -3, -4, -3, -1, -4, -1, -3, -3]
+goddammed	-2.4	0.91652	[-2, -3, -1, -1, -2, -2, -4, -3, -3, -3]
+goddamn	-2.1	1.75784	[-3, -3, -2, -4, -4, -3, -3, -1, 1, 1]
+goddamned	-1.8	2.03961	[-3, -3, -3, -4, -1, 2, -2, -3, 2, -3]
+goddamns	-2.1	1.51327	[-3, -2, -4, 2, -2, -3, -3, -2, -2, -2]
+goddams	-1.9	1.92094	[-3, -3, -2, -4, -4, -2, -3, -1, 2, 1]
+godsend	2.8	0.87178	[2, 3, 3, 2, 4, 3, 3, 1, 4, 3]
+good	1.9	0.9434	[2, 1, 1, 3, 2, 4, 2, 2, 1, 1]
+goodness	2.0	1.54919	[2, 2, 2, 3, 1, 2, -2, 4, 3, 3]
+gorgeous	3.0	0.63246	[3, 3, 2, 3, 3, 3, 4, 4, 3, 2]
+gorgeously	2.3	0.78102	[2, 2, 2, 3, 1, 2, 4, 3, 2, 2]
+gorgeousness	2.9	0.9434	[3, 4, 3, 1, 4, 4, 2, 2, 3, 3]
+gorgeousnesses	2.1	0.7	[3, 2, 1, 3, 2, 2, 1, 2, 3, 2]
+gossip	-0.7	0.45826	[-1, -1, -1, 0, 0, -1, -1, 0, -1, -1]
+gossiped	-1.1	0.53852	[-1, -1, -1, -1, -1, -1, 0, -1, -2, -2]
+gossiper	-1.1	0.7	[-1, -1, -1, 0, -2, -1, -1, -2, 0, -2]
+gossipers	-1.1	0.53852	[-1, 0, -1, -1, -1, -1, -1, -1, -2, -2]
+gossiping	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -1, -2, -2]
+gossipmonger	-1.0	1.41421	[-1, -2, 1, -3, -2, 1, -1, -2, -2, 1]
+gossipmongers	-1.4	0.66332	[-2, -1, -1, -1, -2, -2, -1, 0, -2, -2]
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+greediest	-2.8	0.87178	[-3, -4, -3, -2, -2, -4, -4, -2, -2, -2]
+greedily	-1.9	1.22066	[-2, -1, -3, -3, -3, -2, -1, -2, 1, -3]
+greediness	-1.7	1.00499	[-2, -1, -2, -1, -2, -4, -1, 0, -2, -2]
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+greeting	1.6	0.4899	[2, 1, 2, 2, 1, 2, 2, 1, 1, 2]
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+grievant	-0.8	1.249	[-2, 1, -1, -2, -1, 2, -2, -1, -1, -1]
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+grieve	-1.6	1.49666	[-2, -3, -1, -3, 1, -3, -1, -2, 1, -3]
+grieved	-2.0	0.89443	[-3, -3, -3, -2, -2, -3, -1, -1, -1, -1]
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+grieving	-2.3	1.1	[-2, -4, -2, -3, -3, 0, -3, -2, -1, -3]
+grievous	-2.0	1.84391	[-3, -4, -2, -3, -1, 3, -2, -3, -2, -3]
+grievously	-1.7	1.55242	[-3, -1, -4, -2, -2, 1, -3, 1, -2, -2]
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+guiltily	-1.1	1.57797	[-3, -1, -1, -2, 0, -2, 3, -2, -1, -2]
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+happier	2.4	0.66332	[3, 1, 2, 3, 2, 2, 3, 3, 3, 2]
+happiest	3.2	0.74833	[4, 3, 2, 4, 4, 3, 3, 3, 2, 4]
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+happiness	2.6	0.4899	[2, 3, 3, 3, 3, 2, 2, 3, 2, 3]
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+harassed	-2.5	0.80623	[-4, -2, -3, -3, -2, -2, -3, -2, -3, -1]
+harasser	-2.4	0.8	[-3, -2, -2, -3, -2, -2, -4, -2, -3, -1]
+harassers	-2.8	0.6	[-3, -3, -2, -2, -3, -3, -3, -4, -2, -3]
+harasses	-2.5	0.80623	[-3, -3, -2, -3, -2, -2, -4, -2, -3, -1]
+harassing	-2.5	1.62788	[-2, -4, -3, -4, -3, -3, 2, -2, -3, -3]
+harassment	-2.5	0.67082	[-2, -3, -2, -2, -3, -2, -4, -3, -2, -2]
+harassments	-2.6	0.4899	[-3, -3, -2, -3, -2, -3, -3, -2, -2, -3]
+hard	-0.4	1.2	[0, -1, 0, -1, 0, 1, -2, -1, -2, 2]
+hardier	-0.6	1.68523	[-3, -2, -2, 1, 1, 2, 1, 0, -2, -2]
+hardship	-1.3	1.84662	[-2, 2, -4, -1, -2, -3, -1, -2, 2, -2]
+hardy	1.7	1.00499	[1, 2, 1, 0, 2, 2, 4, 1, 2, 2]
+harm	-2.5	0.80623	[-2, -2, -2, -3, -2, -1, -3, -3, -3, -4]
+harmed	-2.1	0.83066	[-1, -4, -2, -2, -2, -2, -1, -2, -3, -2]
+harmfully	-2.6	0.91652	[-3, -4, -3, -1, -3, -3, -3, -3, -1, -2]
+harmfulness	-2.6	0.8	[-3, -1, -3, -3, -3, -2, -4, -2, -2, -3]
+harming	-2.6	0.66332	[-3, -3, -2, -2, -3, -3, -2, -2, -2, -4]
+harmless	1.0	0.7746	[2, 1, 1, 1, 1, 0, 0, 2, 0, 2]
+harmlessly	1.4	1.2	[4, 0, 1, 0, 1, 1, 1, 2, 3, 1]
+harmlessness	0.8	1.16619	[1, 2, 0, 1, 0, 1, 2, 1, 2, -2]
+harmonic	1.8	0.87178	[2, 1, 2, 3, 0, 1, 3, 2, 2, 2]
+harmonica	0.6	0.8	[0, 1, 0, 0, 0, 2, 1, 0, 2, 0]
+harmonically	2.1	1.13578	[3, 3, 4, 1, 0, 1, 2, 2, 2, 3]
+harmonicas	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+harmonicist	0.5	0.92195	[0, 0, 0, 0, 1, 0, 0, 0, 1, 3]
+harmonicists	0.9	1.3	[2, 1, 0, 0, 2, 0, 0, 0, 4, 0]
+harmonics	1.5	1.0247	[2, 2, 2, 0, 0, 2, 3, 2, 0, 2]
+harmonies	1.3	0.9	[2, 0, 2, 1, 2, 2, 0, 2, 0, 2]
+harmonious	2.0	1.09545	[3, 4, 2, 2, 2, 0, 2, 3, 1, 1]
+harmoniously	1.9	0.9434	[4, 2, 2, 1, 2, 1, 1, 3, 2, 1]
+harmoniousness	1.8	0.6	[1, 2, 2, 2, 2, 1, 2, 3, 2, 1]
+harmonise	1.8	0.74833	[1, 1, 2, 3, 2, 1, 1, 3, 2, 2]
+harmonised	1.3	0.9	[2, 3, 2, 0, 2, 1, 1, 1, 1, 0]
+harmonising	1.4	0.66332	[1, 2, 1, 1, 2, 1, 1, 1, 1, 3]
+harmonium	0.9	1.22066	[0, 3, 0, 2, 3, 0, 0, 0, 0, 1]
+harmoniums	0.8	0.9798	[0, 0, 0, 2, 0, 2, 0, 2, 2, 0]
+harmonization	1.9	0.83066	[3, 1, 2, 2, 2, 2, 3, 0, 2, 2]
+harmonizations	0.9	0.9434	[0, 0, 2, 0, 2, 2, 0, 2, 1, 0]
+harmonize	1.7	0.78102	[3, 2, 2, 1, 2, 2, 0, 1, 2, 2]
+harmonized	1.6	0.91652	[1, 2, 1, 1, 2, 2, 3, 3, 0, 1]
+harmonizer	1.6	0.8	[1, 2, 1, 1, 2, 2, 2, 3, 0, 2]
+harmonizers	1.6	1.11355	[2, 2, 2, 1, 2, 0, 4, 0, 2, 1]
+harmonizes	1.5	0.92195	[0, 2, 2, 2, 0, 1, 1, 2, 3, 2]
+harmonizing	1.4	0.66332	[0, 1, 1, 2, 2, 1, 2, 2, 1, 2]
+harmony	1.7	0.45826	[2, 2, 2, 2, 1, 2, 2, 2, 1, 1]
+harms	-2.2	1.6	[2, -3, -2, -2, -3, -2, -4, -4, -2, -2]
+harried	-1.4	0.4899	[-1, -1, -2, -1, -2, -2, -1, -1, -1, -2]
+harsh	-1.9	0.7	[-1, -1, -2, -2, -1, -3, -3, -2, -2, -2]
+harsher	-2.2	0.6	[-2, -3, -2, -3, -2, -2, -1, -3, -2, -2]
+harshest	-2.9	0.83066	[-4, -2, -2, -2, -2, -3, -3, -4, -4, -3]
+hate	-2.7	1.00499	[-4, -3, -4, -4, -2, -2, -2, -2, -1, -3]
+hated	-3.2	0.6	[-3, -3, -4, -3, -2, -3, -3, -4, -4, -3]
+hateful	-2.2	1.249	[-3, 1, -3, -3, -1, -2, -2, -3, -3, -3]
+hatefully	-2.3	0.78102	[-1, -3, -3, -3, -1, -2, -2, -2, -3, -3]
+hatefulness	-3.6	0.4899	[-4, -4, -3, -3, -3, -4, -4, -4, -4, -3]
+hater	-1.8	0.6	[-2, -1, -2, -2, -2, -1, -1, -2, -2, -3]
+haters	-2.2	0.6	[-2, -1, -3, -2, -3, -2, -3, -2, -2, -2]
+hates	-1.9	0.7	[-2, -1, -2, -2, -3, -1, -1, -2, -2, -3]
+hating	-2.3	1.1	[-4, -3, -4, -1, -2, -2, -1, -2, -1, -3]
+hatred	-3.2	0.9798	[-1, -3, -2, -4, -3, -3, -4, -4, -4, -4]
+haunt	-1.7	1.00499	[-1, -1, -3, -1, -2, -2, -1, -4, -1, -1]
+haunted	-2.1	0.7	[-2, -2, -1, -3, -3, -2, -2, -3, -1, -2]
+haunting	-1.1	0.83066	[-3, 0, -2, -1, 0, -1, -1, -1, -1, -1]
+haunts	-1.0	1.41421	[0, -2, -2, -2, -2, -1, 2, -2, 1, -2]
+havoc	-2.9	0.7	[-2, -4, -4, -3, -2, -3, -3, -3, -2, -3]
+healthy	1.7	0.9	[1, 3, 1, 1, 3, 3, 1, 2, 1, 1]
+heartbreak	-2.7	0.78102	[-1, -3, -3, -3, -2, -4, -2, -3, -3, -3]
+heartbreaker	-2.2	1.07703	[-2, -3, 0, -3, -2, -1, -4, -3, -2, -2]
+heartbreakers	-2.1	0.9434	[-3, -2, -3, -2, -1, -1, -4, -1, -2, -2]
+heartbreaking	-2.0	1.73205	[-3, -1, -3, -3, -4, 2, -3, -2, 0, -3]
+heartbreakingly	-1.8	2.08806	[-3, 3, 1, -3, -3, -2, -3, -3, -4, -1]
+heartbreaks	-1.8	1.77764	[-2, 1, -3, -2, -3, -2, -3, 2, -4, -2]
+heartbroken	-3.3	0.45826	[-4, -3, -3, -4, -3, -3, -4, -3, -3, -3]
+heartfelt	2.5	0.5	[3, 3, 2, 3, 2, 2, 3, 2, 2, 3]
+heartless	-2.2	0.74833	[-2, -2, -2, -4, -2, -1, -2, -3, -2, -2]
+heartlessly	-2.8	0.6	[-3, -2, -3, -3, -2, -3, -4, -2, -3, -3]
+heartlessness	-2.8	0.87178	[-3, -3, -2, -3, -4, -4, -1, -3, -2, -3]
+heartwarming	2.1	1.22066	[3, 2, 3, 3, 2, 2, 3, 3, -1, 1]
+heaven	2.3	1.18743	[1, 1, 2, 4, 3, 3, 3, 4, 1, 1]
+heavenlier	3.0	0.63246	[3, 2, 3, 3, 4, 3, 3, 4, 2, 3]
+heavenliest	2.7	1.1	[3, 2, 3, 4, 2, 4, 3, 0, 3, 3]
+heavenliness	2.7	0.9	[3, 2, 1, 4, 3, 2, 3, 4, 3, 2]
+heavenlinesses	2.3	2.2383	[4, 4, 4, 3, -2, 3, 3, 4, -2, 2]
+heavenly	3.0	0.63246	[3, 3, 3, 3, 2, 3, 3, 4, 2, 4]
+heavens	1.7	1.18743	[4, 0, 1, 2, 0, 3, 2, 2, 2, 1]
+heavenward	1.4	1.35647	[0, 3, 0, 4, 1, 2, 2, 0, 2, 0]
+heavenwards	1.2	1.32665	[1, 4, 0, 0, 2, 1, 1, 0, 3, 0]
+heavyhearted	-2.1	0.83066	[-2, -3, -3, -2, -3, -1, -1, -1, -2, -3]
+heh	-0.6	1.28062	[0, 1, -1, 1, -1, -2, -1, -3, 1, -1]
+hell	-3.6	0.66332	[-4, -4, -4, -4, -4, -2, -3, -4, -3, -4]
+hellish	-3.2	0.74833	[-3, -3, -2, -2, -4, -3, -4, -4, -3, -4]
+help	1.7	0.78102	[3, 2, 1, 2, 1, 2, 3, 1, 1, 1]
+helper	1.4	0.8	[1, 1, 0, 1, 1, 2, 1, 2, 3, 2]
+helpers	1.1	0.83066	[1, 1, 0, 2, 1, 1, 1, 1, 3, 0]
+helpful	1.8	0.87178	[2, 1, 3, 1, 1, 3, 1, 2, 3, 1]
+helpfully	2.3	0.9	[1, 2, 2, 3, 2, 3, 3, 2, 4, 1]
+helpfulness	1.9	1.13578	[1, 4, 1, 2, 2, 1, 1, 2, 4, 1]
+helping	1.2	0.6	[2, 1, 1, 2, 0, 1, 1, 1, 2, 1]
+helpless	-2.0	0.63246	[-2, -3, -2, -2, -2, -3, -1, -2, -1, -2]
+helplessly	-1.4	0.4899	[-1, -1, -2, -2, -1, -1, -1, -2, -2, -1]
+helplessness	-2.1	0.9434	[-2, -4, -1, -2, -1, -3, -3, -2, -1, -2]
+helplessnesses	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -3, -2, -1, -2]
+helps	1.6	0.4899	[1, 1, 1, 2, 2, 2, 1, 2, 2, 2]
+hero	2.6	0.8	[2, 3, 2, 2, 4, 4, 2, 3, 2, 2]
+heroes	2.3	0.9	[3, 4, 3, 1, 3, 2, 1, 2, 2, 2]
+heroic	2.6	0.8	[3, 3, 1, 4, 2, 3, 2, 3, 2, 3]
+heroical	2.9	1.04403	[4, 4, 2, 4, 2, 3, 1, 4, 2, 3]
+heroically	2.4	0.8	[2, 2, 2, 3, 3, 3, 4, 1, 2, 2]
+heroicomic	1.0	1.0	[1, 0, 1, 0, 2, 0, 3, 1, 2, 0]
+heroicomical	1.1	0.83066	[2, 0, 0, 2, 1, 2, 1, 2, 1, 0]
+heroics	2.4	0.8	[2, 1, 2, 2, 2, 3, 3, 3, 4, 2]
+heroin	-2.2	1.83303	[0, -2, -4, 2, -4, -2, -2, -3, -3, -4]
+heroine	2.7	1.1	[0, 2, 4, 4, 3, 3, 3, 3, 2, 3]
+heroines	1.8	1.32665	[2, 1, 1, 4, 3, 1, 0, 3, 3, 0]
+heroinism	-2.0	2.0	[-3, -4, 2, -2, -4, -3, -2, -1, 1, -4]
+heroism	2.8	0.6	[3, 3, 4, 3, 2, 2, 3, 3, 2, 3]
+heroisms	2.2	0.87178	[3, 1, 2, 4, 3, 2, 2, 2, 1, 2]
+heroize	2.1	0.7	[3, 2, 3, 1, 2, 2, 2, 3, 1, 2]
+heroized	2.0	1.18322	[1, 0, 3, 3, 2, 0, 3, 3, 2, 3]
+heroizes	2.2	0.9798	[1, 3, 2, 3, 4, 3, 2, 1, 2, 1]
+heroizing	1.9	1.64012	[2, 3, -2, 2, 4, 3, 2, 2, 3, 0]
+heron	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
+heronries	0.7	1.1	[2, 0, 0, 0, 2, 0, 3, 0, 0, 0]
+heronry	0.1	0.9434	[0, 0, 0, 0, 0, 2, 0, 1, -2, 0]
+herons	0.5	1.0247	[0, 0, 0, 3, 0, 2, 0, 0, 0, 0]
+heros	1.3	1.18743	[3, 0, 0, 2, 0, 2, 2, 3, 1, 0]
+hesitance	-0.9	0.3	[-1, -1, 0, -1, -1, -1, -1, -1, -1, -1]
+hesitancies	-1.0	0.63246	[-1, -1, -1, -2, -1, -1, -2, 0, 0, -1]
+hesitancy	-0.9	0.53852	[0, -1, 0, -2, -1, -1, -1, -1, -1, -1]
+hesitant	-1.0	0.7746	[0, -1, 0, -1, -2, 0, -1, -2, -1, -2]
+hesitantly	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -2, -1, -1]
+hesitate	-1.1	0.53852	[-2, -1, -1, -1, -2, -1, -1, 0, -1, -1]
+hesitated	-1.3	0.9	[-1, -2, -1, -2, -2, -2, -1, 1, -1, -2]
+hesitater	-1.4	0.66332	[-1, -1, -1, -1, -1, -2, -1, -3, -2, -1]
+hesitaters	-1.4	0.4899	[-1, -2, -1, -1, -1, -1, -2, -2, -2, -1]
+hesitates	-1.4	0.4899	[-1, -1, -1, -2, -1, -2, -1, -2, -2, -1]
+hesitating	-1.4	0.66332	[-1, -1, -2, -1, -1, -3, -2, -1, -1, -1]
+hesitatingly	-1.5	0.80623	[-1, -1, -1, -1, -3, -2, -3, -1, -1, -1]
+hesitation	-1.1	0.53852	[-2, 0, -1, -1, -1, -1, -1, -2, -1, -1]
+hesitations	-1.1	0.53852	[-1, -1, -1, 0, -2, -1, -1, -2, -1, -1]
+hid	-0.4	0.4899	[0, -1, 0, 0, -1, -1, -1, 0, 0, 0]
+hide	-0.7	0.64031	[0, -1, -1, -1, -1, 0, 0, -2, -1, 0]
+hides	-0.7	0.9	[-1, -2, -1, 0, -1, 0, 0, -2, 1, -1]
+hiding	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -1, -2, -1]
+highlight	1.4	0.91652	[3, 0, 1, 1, 2, 1, 0, 2, 2, 2]
+hilarious	1.7	1.41774	[2, 2, 2, 3, 3, 1, -2, 2, 3, 1]
+hindrance	-1.7	0.78102	[-2, -3, -2, -1, -1, -1, -3, -1, -2, -1]
+hoax	-1.1	1.04403	[-3, -1, -2, -1, 1, -2, -1, -1, -1, 0]
+holiday	1.7	1.18743	[1, 3, 2, 2, 0, 0, 1, 2, 4, 2]
+holidays	1.6	1.0198	[2, 0, 1, 2, 3, 0, 1, 2, 3, 2]
+homesick	-0.7	1.67631	[-2, -1, -1, -2, -1, -2, 2, -1, 3, -2]
+homesickness	-1.8	1.249	[-3, -2, -1, -1, -3, -2, -1, 1, -3, -3]
+homesicknesses	-1.8	0.6	[-1, -2, -2, -2, -1, -2, -1, -2, -3, -2]
+honest	2.3	0.9	[3, 2, 1, 2, 3, 1, 2, 3, 2, 4]
+honester	1.9	0.7	[2, 3, 2, 2, 1, 3, 1, 1, 2, 2]
+honestest	3.0	0.7746	[1, 3, 3, 3, 3, 3, 4, 4, 3, 3]
+honesties	1.8	1.07703	[4, 3, 1, 1, 1, 1, 3, 2, 1, 1]
+honestly	2.0	0.63246	[2, 3, 2, 2, 1, 2, 2, 1, 3, 2]
+honesty	2.2	0.6	[2, 3, 2, 2, 1, 2, 3, 2, 3, 2]
+honor	2.2	1.16619	[3, 2, 1, 2, 0, 4, 3, 1, 3, 3]
+honorability	2.2	0.4	[3, 3, 2, 2, 2, 2, 2, 2, 2, 2]
+honorable	2.5	0.67082	[2, 2, 3, 2, 4, 3, 2, 2, 2, 3]
+honorableness	2.2	0.87178	[2, 4, 1, 3, 3, 2, 1, 2, 2, 2]
+honorably	2.4	0.66332	[2, 2, 3, 2, 3, 3, 3, 1, 2, 3]
+honoraria	0.6	0.8	[1, 0, 1, 0, 0, 0, 2, 0, 2, 0]
+honoraries	1.5	1.5	[2, 2, 1, 3, 3, 1, -2, 2, 3, 0]
+honorarily	1.9	0.7	[2, 2, 3, 1, 2, 1, 2, 1, 3, 2]
+honorarium	0.7	1.48661	[3, 2, -1, 2, 1, -2, 1, 1, -1, 1]
+honorariums	1.0	1.0	[0, 0, 0, 0, 1, 2, 1, 3, 2, 1]
+honorary	1.4	0.91652	[2, 2, 2, 3, 1, 1, 0, 1, 2, 0]
+honored	2.8	0.87178	[3, 4, 4, 3, 1, 2, 2, 3, 3, 3]
+honoree	2.1	0.7	[3, 2, 3, 3, 1, 2, 1, 2, 2, 2]
+honorees	2.3	0.78102	[1, 3, 3, 4, 2, 2, 2, 2, 2, 2]
+honorer	1.7	0.78102	[2, 1, 3, 3, 1, 2, 1, 2, 1, 1]
+honorers	1.3	0.45826	[1, 1, 2, 2, 1, 1, 2, 1, 1, 1]
+honorific	1.4	1.2	[2, 2, 2, 2, 2, 1, 2, 1, 2, -2]
+honorifically	2.2	0.74833	[3, 4, 1, 2, 2, 2, 2, 2, 2, 2]
+honorifics	1.7	0.78102	[1, 2, 0, 1, 2, 2, 2, 3, 2, 2]
+honoring	2.3	0.64031	[3, 3, 1, 2, 2, 3, 3, 2, 2, 2]
+honors	2.3	0.64031	[3, 2, 2, 2, 1, 3, 3, 2, 3, 2]
+honour	2.7	0.78102	[2, 3, 2, 2, 2, 3, 4, 4, 3, 2]
+honourable	2.1	0.53852	[2, 3, 2, 2, 2, 1, 3, 2, 2, 2]
+honoured	2.2	1.249	[3, 3, 4, 3, -1, 2, 2, 2, 2, 2]
+honourer	1.8	0.87178	[2, 3, 2, 1, 2, 3, 1, 0, 2, 2]
+honourers	1.6	1.0198	[0, 2, 2, 1, 2, 2, 1, 3, 0, 3]
+honouring	2.1	0.3	[2, 2, 2, 3, 2, 2, 2, 2, 2, 2]
+honours	2.2	0.87178	[4, 3, 2, 2, 3, 2, 2, 1, 2, 1]
+hooligan	-1.5	0.5	[-1, -2, -1, -2, -2, -2, -1, -1, -2, -1]
+hooliganism	-2.1	0.83066	[-3, -2, -3, -3, -2, -2, -2, -2, 0, -2]
+hooligans	-1.1	1.22066	[-2, -1, -1, 2, -1, -1, -1, -3, -2, -1]
+hooray	2.3	0.9	[3, 2, 3, 2, 1, 3, 1, 2, 2, 4]
+hope	1.9	0.53852	[3, 2, 2, 1, 2, 2, 1, 2, 2, 2]
+hoped	1.6	0.4899	[1, 2, 1, 1, 2, 2, 1, 2, 2, 2]
+hopeful	2.3	0.78102	[2, 1, 1, 3, 3, 3, 2, 3, 2, 3]
+hopefully	1.7	0.78102	[1, 3, 1, 3, 1, 2, 1, 1, 2, 2]
+hopefulness	1.6	1.35647	[2, 1, -2, 2, 3, 2, 1, 3, 2, 2]
+hopeless	-2.0	1.78885	[-3, -3, -3, -3, 3, -1, -3, -3, -2, -2]
+hopelessly	-2.2	0.74833	[-3, -4, -2, -2, -1, -2, -2, -2, -2, -2]
+hopelessness	-3.1	0.7	[-3, -4, -4, -3, -3, -3, -4, -3, -2, -2]
+hopes	1.8	0.6	[1, 3, 1, 2, 2, 2, 1, 2, 2, 2]
+hoping	1.8	0.4	[2, 2, 2, 1, 2, 2, 2, 2, 2, 1]
+horrendous	-2.8	0.87178	[-3, -3, -4, -4, -3, -3, -2, -2, -1, -3]
+horrendously	-1.9	1.92094	[-3, -2, -4, -4, 2, -1, -3, -2, 1, -3]
+horrent	-0.9	1.04403	[0, -1, -2, 0, 0, -3, -1, 0, -2, 0]
+horrible	-2.5	0.67082	[-2, -2, -3, -2, -2, -4, -3, -3, -2, -2]
+horribleness	-2.4	0.4899	[-3, -3, -2, -2, -3, -2, -2, -3, -2, -2]
+horribles	-2.1	0.7	[-2, -4, -2, -2, -1, -2, -2, -2, -2, -2]
+horribly	-2.4	0.66332	[-2, -2, -2, -2, -2, -4, -3, -3, -2, -2]
+horrid	-2.5	1.0247	[-2, -3, -3, -4, -4, -1, -2, -2, -3, -1]
+horridly	-1.4	1.49666	[-2, 0, -3, -2, 0, -3, 2, -2, -2, -2]
+horridness	-2.3	1.26886	[-3, -3, -2, 1, -3, -3, -3, -3, -1, -3]
+horridnesses	-3.0	1.09545	[-2, -3, -4, -4, -4, -4, -2, -2, -1, -4]
+horrific	-3.4	0.91652	[-2, -4, -4, -4, -2, -4, -2, -4, -4, -4]
+horrifically	-2.9	0.7	[-2, -3, -2, -4, -2, -4, -3, -3, -3, -3]
+horrified	-2.5	0.92195	[-2, -3, -2, -2, -1, -4, -2, -2, -3, -4]
+horrifies	-2.9	1.22066	[-1, -3, -2, -1, -4, -4, -4, -4, -2, -4]
+horrify	-2.5	0.67082	[-2, -2, -3, -2, -2, -2, -4, -2, -3, -3]
+horrifying	-2.7	0.9	[-3, -4, -3, -2, -3, -3, -4, -2, -2, -1]
+horrifyingly	-3.3	0.9	[-3, -3, -4, -4, -1, -4, -3, -3, -4, -4]
+horror	-2.7	1.1	[-3, -1, -4, -4, -4, -3, -1, -2, -3, -2]
+horrors	-2.7	0.64031	[-3, -3, -4, -3, -2, -2, -2, -3, -2, -3]
+hostile	-1.6	1.74356	[-4, -3, -3, -1, 1, -2, 2, -2, -2, -2]
+hostilely	-2.2	0.6	[-1, -3, -3, -2, -2, -2, -2, -2, -2, -3]
+hostiles	-1.3	1.9	[-3, -3, -3, -3, -1, 2, -3, -1, 1, 1]
+hostilities	-2.1	0.53852	[-2, -3, -2, -2, -2, -2, -1, -2, -3, -2]
+hostility	-2.5	0.80623	[-2, -2, -3, -3, -3, -2, -4, -2, -3, -1]
+huckster	-0.9	0.7	[-1, 0, -1, 0, -1, -2, -2, 0, -1, -1]
+hug	2.1	1.04403	[1, 3, 2, 1, 1, 2, 3, 3, 1, 4]
+huge	1.3	0.9	[0, 2, 2, 0, 0, 2, 2, 2, 1, 2]
+huggable	1.6	0.66332	[2, 2, 1, 1, 1, 3, 1, 2, 2, 1]
+hugged	1.7	0.78102	[2, 2, 2, 2, 3, 1, 1, 2, 0, 2]
+hugger	1.6	0.91652	[3, 2, 2, 2, 3, 1, 1, 1, 0, 1]
+huggers	1.8	0.6	[1, 3, 1, 2, 1, 2, 2, 2, 2, 2]
+hugging	1.8	0.74833	[2, 1, 1, 3, 3, 2, 2, 1, 2, 1]
+hugs	2.2	0.74833	[3, 2, 1, 2, 2, 2, 3, 1, 3, 3]
+humerous	1.4	1.11355	[-1, 2, 2, 3, 1, 1, 2, 0, 2, 2]
+humiliate	-2.5	1.28452	[-3, -3, -3, -3, -2, -2, -4, -3, 1, -3]
+humiliated	-1.4	2.498	[3, -3, -4, -3, -3, -4, -3, 0, 1, 2]
+humiliates	-1.0	2.09762	[1, -2, -3, -3, -3, -2, -3, 1, 2, 2]
+humiliating	-1.2	1.8868	[-4, -1, -3, -1, 2, -1, 2, -3, -2, -1]
+humiliatingly	-2.6	0.4899	[-3, -3, -2, -2, -3, -3, -3, -3, -2, -2]
+humiliation	-2.7	0.78102	[-2, -3, -4, -2, -2, -2, -3, -2, -4, -3]
+humiliations	-2.4	0.66332	[-3, -2, -2, -2, -2, -2, -2, -3, -2, -4]
+humor	1.1	0.53852	[1, 0, 2, 2, 1, 1, 1, 1, 1, 1]
+humoral	0.6	1.0198	[2, 0, 0, 0, 0, 0, 3, 1, 0, 0]
+humored	1.2	0.87178	[1, 1, 2, 2, 1, 1, 2, 1, 2, -1]
+humoresque	1.2	0.6	[1, 1, 1, 2, 1, 2, 2, 1, 1, 0]
+humoresques	0.9	1.04403	[1, 0, 2, 0, 0, 1, 2, 0, 3, 0]
+humoring	2.1	0.7	[3, 2, 2, 2, 1, 2, 2, 1, 3, 3]
+humorist	1.2	0.74833	[1, 2, 1, 1, 2, 1, 2, 0, 0, 2]
+humoristic	1.5	0.80623	[3, 0, 2, 1, 2, 1, 2, 2, 1, 1]
+humorists	1.3	0.78102	[2, 1, 1, 1, 0, 1, 2, 3, 1, 1]
+humorless	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -2]
+humorlessness	-1.4	1.11355	[1, -3, -3, -1, -1, -2, -1, -1, -2, -1]
+humorous	1.6	0.4899	[1, 2, 1, 2, 2, 1, 2, 2, 1, 2]
+humorously	2.3	0.78102	[3, 3, 2, 2, 1, 3, 3, 1, 2, 3]
+humorousness	2.4	0.66332	[1, 2, 3, 2, 3, 2, 3, 3, 2, 3]
+humors	1.6	0.4899	[2, 1, 2, 2, 2, 2, 1, 2, 1, 1]
+humour	2.1	0.9434	[1, 2, 2, 4, 2, 1, 1, 3, 3, 2]
+humoured	1.1	0.53852	[1, 0, 1, 2, 2, 1, 1, 1, 1, 1]
+humouring	1.7	0.78102	[2, 3, 1, 2, 1, 0, 2, 2, 2, 2]
+humourous	2.0	0.7746	[1, 2, 3, 2, 2, 3, 3, 2, 1, 1]
+hunger	-1.0	1.67332	[-4, 0, 2, -2, -1, -2, 1, -2, 0, -2]
+hurrah	2.6	0.8	[3, 2, 3, 3, 1, 3, 4, 2, 2, 3]
+hurrahed	1.9	0.53852	[2, 2, 1, 1, 2, 2, 3, 2, 2, 2]
+hurrahing	2.4	0.4899	[3, 2, 2, 2, 3, 2, 3, 3, 2, 2]
+hurrahs	2.1	1.44568	[2, 3, 0, 3, 2, 3, -1, 2, 3, 4]
+hurray	2.7	0.78102	[3, 2, 3, 3, 1, 3, 4, 2, 3, 3]
+hurrayed	1.8	1.32665	[3, 3, 2, 3, 3, 3, 0, 0, 1, 0]
+hurraying	1.2	1.66132	[2, -3, 2, 3, 0, 2, 2, 2, 0, 2]
+hurrays	2.4	1.11355	[2, 3, 2, 4, 0, 3, 2, 2, 2, 4]
+hurt	-2.4	0.8	[-3, -3, -2, -2, -4, -3, -2, -1, -2, -2]
+hurter	-2.3	0.78102	[-2, -4, -1, -2, -3, -3, -2, -2, -2, -2]
+hurters	-1.9	1.04403	[-2, -3, -1, -2, -1, 0, -3, -3, -3, -1]
+hurtful	-2.4	1.0198	[-2, -4, -2, -2, -1, -3, -2, -3, -1, -4]
+hurtfully	-2.6	0.66332	[-3, -2, -3, -2, -2, -3, -4, -3, -2, -2]
+hurtfulness	-1.9	1.51327	[2, -2, -2, -2, -3, -1, -2, -3, -4, -2]
+hurting	-1.7	0.78102	[-3, -1, -1, -2, -1, -1, -3, -2, -2, -1]
+hurtle	-0.3	1.1	[-2, 1, 0, -1, -1, -1, 0, 2, 0, -1]
+hurtled	-0.6	0.8	[0, -2, 0, 0, 0, 0, -1, -1, -2, 0]
+hurtles	-1.0	0.63246	[-1, -2, 0, 0, -1, -1, -1, -1, -2, -1]
+hurtless	0.3	1.55242	[-1, -3, 2, 1, 2, 1, 0, 0, -1, 2]
+hurtling	-1.4	0.8	[-3, -2, -1, -1, -1, -1, -1, -2, 0, -2]
+hurts	-2.1	0.83066	[-4, -2, -2, -2, -3, -1, -2, -2, -2, -1]
+hypocritical	-2.0	0.89443	[-4, -2, -1, -3, -2, -1, -2, -1, -2, -2]
+hysteria	-1.9	0.7	[-1, -3, -1, -2, -2, -2, -2, -2, -1, -3]
+hysterical	-0.1	1.97231	[2, 0, 0, 3, -2, -2, 3, -1, -2, -2]
+hysterics	-1.8	1.77764	[-3, -3, -3, -1, -3, -1, -2, 3, -3, -2]
+ideal	2.4	1.2	[4, 3, 4, 4, 2, 2, 1, 2, 1, 1]
+idealess	-1.9	1.3	[-4, -2, -3, -2, -1, 0, -4, -1, -1, -1]
+idealise	1.4	0.91652	[2, 2, 1, 0, 1, 3, 2, 0, 1, 2]
+idealised	2.1	0.83066	[1, 4, 1, 3, 2, 2, 2, 2, 2, 2]
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+idealising	0.6	0.4899	[0, 1, 1, 1, 1, 1, 1, 0, 0, 0]
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+idealisms	0.8	0.9798	[0, 2, 3, 1, 0, 0, 1, 0, 0, 1]
+idealist	1.6	1.56205	[2, 3, -2, 1, 3, 3, 1, 0, 2, 3]
+idealistic	1.8	0.9798	[2, 1, 0, 2, 4, 2, 2, 2, 1, 2]
+idealistically	1.7	1.1	[0, 3, 3, 1, 2, 3, 0, 2, 1, 2]
+idealists	0.7	1.1	[0, -2, 1, 2, 1, 1, 2, 0, 1, 1]
+idealities	1.5	0.67082	[2, 1, 1, 2, 1, 0, 2, 2, 2, 2]
+ideality	1.9	0.9434	[0, 1, 2, 3, 2, 1, 2, 3, 3, 2]
+idealization	1.8	0.9798	[2, 2, 2, 1, 4, 2, 2, 0, 1, 2]
+idealizations	1.4	0.66332	[2, 1, 1, 2, 1, 2, 1, 0, 2, 2]
+idealize	1.2	0.9798	[1, 2, 2, 0, 0, 1, 3, 0, 2, 1]
+idealized	1.8	0.74833	[2, 3, 1, 1, 2, 1, 3, 1, 2, 2]
+idealizer	1.3	0.9	[1, 1, 1, 1, 1, 3, 0, 1, 3, 1]
+idealizers	1.9	1.37477	[1, 4, 1, 2, 0, 2, 3, 2, 4, 0]
+idealizes	2.0	1.0	[3, 2, 2, 1, 4, 2, 2, 0, 2, 2]
+idealizing	1.4	1.0198	[1, 1, 2, 3, 0, 1, 3, 0, 2, 1]
+idealless	-1.7	1.00499	[-2, -2, -2, -2, -4, -1, 0, -1, -2, -1]
+ideally	1.8	1.16619	[1, 0, 2, 2, 3, 2, 4, 0, 2, 2]
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+idealogy	0.8	1.16619	[0, 3, 1, 0, 2, 0, 0, 1, 2, -1]
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+idiot	-2.3	0.64031	[-2, -3, -1, -3, -2, -3, -3, -2, -2, -2]
+idiotic	-2.6	0.91652	[-3, -4, -2, -3, -2, -2, -4, -1, -3, -2]
+ignorable	-1.0	0.63246	[-1, -1, -1, -2, 0, -1, 0, -1, -2, -1]
+ignorami	-1.9	0.83066	[-2, -2, -3, -2, 0, -1, -2, -2, -3, -2]
+ignoramus	-1.9	0.83066	[-1, -2, -1, -3, -1, -3, -1, -3, -2, -2]
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+ignorance	-1.5	1.20416	[-2, -2, -3, -2, 0, -2, -1, -3, -1, 1]
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+ignorant	-1.1	0.83066	[-1, -1, -1, -2, 1, -2, -1, -2, -1, -1]
+ignorantly	-1.6	0.91652	[-1, -2, -2, -2, -2, -2, -2, 1, -2, -2]
+ignorantness	-1.1	1.44568	[3, -1, -2, -1, -1, -2, -2, -2, -1, -2]
+ignore	-1.5	0.67082	[-1, -2, -1, -1, -1, -1, -2, -3, -2, -1]
+ignored	-1.3	0.45826	[-2, -1, -2, -1, -1, -2, -1, -1, -1, -1]
+ignorer	-1.3	0.45826	[-1, -1, -2, -1, -2, -1, -1, -1, -2, -1]
+ignorers	-0.7	1.00499	[-1, -2, -1, -1, -1, 1, 0, -2, 1, -1]
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+ignoring	-1.7	0.64031	[-1, -1, -1, -2, -2, -3, -2, -1, -2, -2]
+ill	-1.8	0.9798	[-2, 0, -2, -1, -4, -2, -2, -2, -1, -2]
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+immobilized	-1.2	0.87178	[-1, -3, 0, -1, -1, 0, -2, -1, -2, -1]
+immoral	-2.0	1.09545	[-4, -1, -1, -3, -2, -3, -3, -1, -1, -1]
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+immoralities	-1.1	1.51327	[-2, -1, -4, -3, 1, 1, -1, 0, -1, -1]
+immorality	-0.6	2.2891	[3, -3, 1, 2, 2, -2, -4, -1, -2, -2]
+immorally	-2.1	0.7	[-1, -1, -2, -2, -3, -2, -3, -2, -2, -3]
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+impatiently	-1.7	0.64031	[-1, -1, -2, -3, -1, -2, -1, -2, -2, -2]
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+impolite	-1.6	0.66332	[-2, -1, -3, -1, -1, -1, -1, -2, -2, -2]
+impolitely	-1.8	0.6	[-2, -2, -1, -1, -2, -1, -2, -2, -3, -2]
+impoliteness	-1.8	0.87178	[-1, -3, -2, -3, -2, -3, -1, -1, -1, -1]
+impolitenesses	-2.3	0.78102	[-3, -2, -2, -1, -1, -3, -3, -2, -3, -3]
+importance	1.5	0.80623	[2, 1, 2, 3, 1, 2, 1, 0, 2, 1]
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+importancy	1.4	0.66332	[2, 1, 2, 2, 1, 2, 1, 0, 2, 1]
+important	0.8	1.07703	[0, 0, 0, 2, 1, 0, 0, 3, 2, 0]
+importantly	1.3	0.78102	[2, 1, 2, 1, 2, 2, 0, 0, 1, 2]
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+imposed	-0.3	1.41774	[2, -1, -1, -1, 1, 0, -2, 2, -2, -1]
+imposes	-0.4	1.42829	[-2, -1, 1, -2, -1, -1, -2, 1, 2, 1]
+imposing	-0.4	1.0198	[1, -1, -2, -1, 1, 1, 0, -1, -1, -1]
+impotent	-1.1	0.3	[-1, -1, -1, -2, -1, -1, -1, -1, -1, -1]
+impress	1.9	0.53852	[2, 2, 1, 2, 2, 2, 2, 1, 2, 3]
+impressed	2.1	0.3	[2, 2, 2, 2, 2, 2, 3, 2, 2, 2]
+impresses	2.1	0.3	[2, 2, 2, 2, 2, 2, 3, 2, 2, 2]
+impressibility	1.2	1.249	[-1, 2, 0, 2, 0, 2, 2, 3, 2, 0]
+impressible	0.8	1.16619	[2, -1, 1, 0, -1, 2, 1, 0, 2, 2]
+impressing	2.5	0.92195	[3, 4, 1, 2, 3, 2, 3, 1, 3, 3]
+impression	0.9	0.9434	[0, 1, 0, 0, 2, 2, 0, 2, 0, 2]
+impressionable	0.2	1.07703	[0, 0, -1, 1, -1, -1, 0, 2, 0, 2]
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+impressionisms	0.5	0.80623	[0, 0, 0, 0, 0, 2, 0, 1, 0, 2]
+impressionist	1.0	1.09545	[0, 2, 3, 0, 0, 2, 2, 0, 1, 0]
+impressionistic	1.5	1.20416	[2, 2, 0, 0, 1, 0, 2, 2, 4, 2]
+impressionistically	1.6	0.8	[2, 0, 1, 1, 2, 2, 3, 2, 2, 1]
+impressionists	0.5	1.43178	[2, 0, 0, 1, 1, 2, -2, 2, 1, -2]
+impressions	0.9	1.13578	[2, 0, 0, 3, 0, 2, 0, 2, 0, 0]
+impressive	2.3	0.78102	[1, 2, 3, 2, 3, 2, 3, 3, 3, 1]
+impressively	2.0	0.89443	[3, 1, 1, 2, 2, 2, 2, 4, 2, 1]
+impressiveness	1.7	0.64031	[2, 1, 2, 3, 1, 2, 2, 2, 1, 1]
+impressment	-0.4	1.85472	[-2, 1, 3, -2, -1, -3, 0, 0, 2, -2]
+impressments	0.5	1.20416	[2, 0, 0, 1, 2, 2, 0, -2, 0, 0]
+impressure	0.6	1.0198	[-1, 0, 0, 0, 0, 2, 0, 2, 1, 2]
+imprisoned	-2.0	1.0	[-4, -2, -3, -1, -3, -2, -1, -2, -1, -1]
+improve	1.9	0.7	[2, 3, 3, 2, 1, 1, 2, 2, 1, 2]
+improved	2.1	0.7	[3, 1, 2, 3, 2, 3, 1, 2, 2, 2]
+improvement	2.0	0.63246	[2, 3, 3, 2, 1, 1, 2, 2, 2, 2]
+improvements	1.3	0.64031	[0, 2, 2, 1, 2, 2, 1, 1, 1, 1]
+improver	1.8	0.6	[2, 1, 2, 1, 2, 3, 1, 2, 2, 2]
+improvers	1.3	0.78102	[1, 2, 2, 1, 2, 2, 0, 0, 1, 2]
+improves	1.8	1.07703	[3, -1, 2, 2, 2, 3, 1, 2, 2, 2]
+improving	1.8	0.4	[2, 2, 1, 1, 2, 2, 2, 2, 2, 2]
+inability	-1.7	0.9	[-2, -2, -3, 0, -2, -3, -2, -1, -1, -1]
+inaction	-1.0	0.63246	[-2, -1, 0, -1, -1, 0, -1, -2, -1, -1]
+inadequacies	-1.7	0.64031	[-1, -3, -2, -1, -2, -1, -2, -2, -1, -2]
+inadequacy	-1.7	0.78102	[-1, -3, -1, -1, -3, -2, -2, -1, -2, -1]
+inadequate	-1.7	0.64031	[-2, -1, -1, -3, -1, -1, -2, -2, -2, -2]
+inadequately	-1.0	1.26491	[-3, -1, -1, -2, 2, -1, -2, -1, 0, -1]
+inadequateness	-1.7	0.45826	[-2, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+inadequatenesses	-1.6	0.91652	[-1, -1, -2, -1, -2, -4, -2, -1, -1, -1]
+incapable	-1.6	0.4899	[-1, -2, -1, -1, -2, -1, -2, -2, -2, -2]
+incapacitated	-1.9	0.9434	[-2, -2, -1, -1, -2, -4, -1, -1, -2, -3]
+incensed	-2.0	1.0	[-2, -1, -4, 0, -2, -2, -2, -3, -2, -2]
+incentive	1.5	1.0247	[1, 2, 1, 2, 1, 0, 4, 2, 1, 1]
+incentives	1.3	1.34536	[2, 2, 1, 1, 3, 1, -2, 3, 1, 1]
+incompetence	-2.3	0.45826	[-3, -2, -2, -3, -2, -3, -2, -2, -2, -2]
+incompetent	-2.1	0.83066	[-1, -1, -2, -2, -3, -3, -2, -3, -1, -3]
+inconsiderate	-1.9	0.7	[-2, -1, -1, -1, -2, -2, -2, -3, -3, -2]
+inconvenience	-1.5	0.5	[-1, -2, -1, -1, -1, -2, -2, -1, -2, -2]
+inconvenient	-1.4	0.4899	[-2, -2, -1, -2, -1, -2, -1, -1, -1, -1]
+increase	1.3	0.64031	[1, 2, 2, 1, 2, 0, 1, 1, 2, 1]
+increased	1.1	1.04403	[2, 0, 3, 2, 2, 1, 0, 1, 0, 0]
+indecision	-0.8	0.6	[-1, 0, -1, 0, -1, -1, -2, 0, -1, -1]
+indecisions	-1.1	0.53852	[-1, -1, -1, -1, -2, -1, -2, -1, 0, -1]
+indecisive	-1.0	0.44721	[0, -1, -1, -1, -1, -2, -1, -1, -1, -1]
+indecisively	-0.7	1.18743	[-2, -1, -1, -1, -1, -1, -2, 2, 1, -1]
+indecisiveness	-1.3	0.64031	[-1, -3, -1, -2, -1, -1, -1, -1, -1, -1]
+indecisivenesses	-0.9	0.53852	[-1, -1, 0, -1, -1, 0, -1, -2, -1, -1]
+indestructible	0.6	1.85472	[3, 4, -1, -2, 1, 1, 2, 0, -1, -1]
+indifference	-0.2	0.74833	[0, -1, 0, 0, 0, 1, -2, 0, 0, 0]
+indifferent	-0.8	0.6	[-1, 0, 0, -1, -2, -1, -1, 0, -1, -1]
+indignant	-1.8	0.74833	[-1, -3, -2, -2, -2, -1, -1, -1, -3, -2]
+indignation	-2.4	0.8	[-2, -1, -2, -3, -3, -3, -1, -3, -3, -3]
+indoctrinate	-1.4	0.91652	[-1, -3, -1, 0, -2, -1, -2, -2, 0, -2]
+indoctrinated	-0.4	1.35647	[1, -2, -3, 1, -1, 1, 1, -1, -1, 0]
+indoctrinates	-0.6	1.2	[1, -1, -3, 1, -1, 1, -1, -1, -1, -1]
+indoctrinating	-0.7	1.41774	[-1, 0, -3, -1, -2, -1, 2, -2, 0, 1]
+ineffective	-0.5	1.74642	[-2, -1, -1, -1, -2, 2, -2, 1, 3, -2]
+ineffectively	-1.3	0.9	[-2, -2, -2, 1, -1, -1, -1, -2, -1, -2]
+ineffectiveness	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -1, -2, -1]
+ineffectual	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+ineffectuality	-1.6	0.66332	[-2, -1, -1, -1, -2, -1, -3, -2, -2, -1]
+ineffectually	-1.1	0.9434	[-1, -2, -2, -1, 0, -1, -2, -1, 1, -2]
+ineffectualness	-1.3	0.45826	[-2, -1, -1, -1, -1, -2, -1, -1, -2, -1]
+infatuated	0.2	1.72047	[3, 2, 0, 3, -1, -1, -2, 0, -1, -1]
+infatuation	0.6	1.74356	[1, -1, -1, 2, -1, 1, 4, 2, 1, -2]
+infected	-2.2	0.6	[-3, -2, -2, -2, -2, -2, -3, -1, -2, -3]
+inferior	-1.7	0.78102	[-1, -2, -2, -1, -1, -3, -2, -1, -1, -3]
+inferiorities	-1.9	0.7	[-2, -3, -1, -2, -2, -3, -1, -1, -2, -2]
+inferiority	-1.1	1.7	[-2, -3, -2, -2, -2, -3, 2, 1, -1, 1]
+inferiorly	-2.0	0.63246	[-3, -2, -2, -2, -2, -3, -1, -2, -1, -2]
+inferiors	-0.5	1.43178	[-1, -1, -1, -2, -1, 0, 3, -1, 1, -2]
+inflamed	-1.4	1.28062	[-2, -2, -1, -2, -2, -1, 2, -3, -2, -1]
+influential	1.9	1.04403	[3, 1, 2, 3, 4, 1, 1, 2, 1, 1]
+infringement	-2.1	0.83066	[-3, -1, -2, -1, -2, -1, -3, -3, -2, -3]
+infuriate	-2.2	0.87178	[-2, -1, -3, -3, -2, -3, -3, -1, -1, -3]
+infuriated	-3.0	0.7746	[-1, -4, -3, -3, -3, -3, -3, -3, -3, -4]
+infuriates	-2.6	0.8	[-4, -2, -1, -3, -3, -3, -2, -3, -3, -2]
+infuriating	-2.4	1.42829	[-1, -3, -3, -3, -3, -4, 0, 0, -4, -3]
+inhibin	-0.2	0.4	[-1, 0, 0, 0, 0, 0, 0, 0, -1, 0]
+inhibit	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -2]
+inhibited	-0.4	0.4899	[0, 0, -1, 0, -1, -1, 0, -1, 0, 0]
+inhibiting	-0.4	1.42829	[1, -1, -1, -1, -2, -1, 2, -2, 2, -1]
+inhibition	-1.5	0.67082	[-1, -1, -1, -1, -2, -1, -1, -2, -2, -3]
+inhibitions	-0.8	0.74833	[-2, -1, -2, 0, 0, 0, 0, -1, -1, -1]
+inhibitive	-1.4	0.4899	[-2, -2, -1, -1, -2, -1, -2, -1, -1, -1]
+inhibitor	-0.3	1.00499	[-2, 1, 1, -1, 1, 0, -1, -1, 0, -1]
+inhibitors	-1.0	0.7746	[-1, 0, -2, -1, -2, -2, 0, 0, -1, -1]
+inhibitory	-1.0	0.7746	[0, -1, -2, -2, -1, -2, 0, 0, -1, -1]
+inhibits	-0.9	0.53852	[-1, -1, -2, -1, -1, 0, -1, -1, -1, 0]
+injured	-1.7	0.64031	[-2, -1, -1, -1, -2, -1, -2, -2, -3, -2]
+injury	-1.8	0.6	[-2, -2, -1, -2, -1, -1, -2, -3, -2, -2]
+injustice	-2.7	0.64031	[-3, -2, -3, -4, -3, -3, -2, -2, -3, -2]
+innocence	1.6	0.91652	[3, 1, 1, 1, 2, 2, 0, 3, 2, 1]
+innocency	1.9	0.83066	[3, 1, 2, 0, 2, 2, 2, 3, 2, 2]
+innocent	1.4	1.2	[1, -1, 2, 2, 2, 0, 1, 3, 3, 1]
+innocenter	0.9	1.37477	[1, 1, 1, 2, 2, 1, 1, -3, 1, 2]
+innocently	1.4	0.8	[0, 2, 1, 1, 1, 1, 3, 2, 2, 1]
+innocents	1.1	1.04403	[0, 0, 2, 2, 2, -1, 1, 1, 2, 2]
+innovate	2.2	0.74833	[2, 4, 3, 2, 2, 1, 2, 2, 2, 2]
+innovates	2.0	0.89443	[2, 2, 2, 0, 1, 3, 3, 2, 3, 2]
+innovation	1.6	0.91652	[1, 0, 3, 2, 1, 2, 3, 2, 1, 1]
+innovative	1.9	0.83066	[1, 1, 2, 1, 2, 4, 2, 2, 2, 2]
+inquisition	-1.2	1.249	[-2, 1, -1, 0, 0, -3, -1, -3, -2, -1]
+inquisitive	0.7	1.18743	[2, 1, 1, 2, -2, -1, 1, 1, 1, 1]
+insane	-1.7	0.78102	[-2, 0, -2, -1, -2, -3, -2, -2, -1, -2]
+insanity	-2.7	1.00499	[-2, -4, -1, -1, -3, -4, -3, -3, -3, -3]
+insecure	-1.8	0.74833	[-1, -2, -2, -1, -3, -2, -3, -2, -1, -1]
+insecurely	-1.4	0.66332	[-3, -1, -1, -1, -2, -1, -2, -1, -1, -1]
+insecureness	-1.8	0.87178	[-1, -1, -1, -3, -3, -3, -2, -2, -1, -1]
+insecurities	-1.8	0.6	[-3, -2, -2, -2, -1, -2, -1, -1, -2, -2]
+insecurity	-1.8	0.74833	[-2, -2, -2, -1, -3, -3, -2, -1, -1, -1]
+insensitive	-0.9	1.81384	[2, -3, -2, -1, 2, -3, -2, 1, -1, -2]
+insensitivity	-1.8	0.6	[-2, -2, -1, -3, -2, -2, -1, -2, -1, -2]
+insignificant	-1.4	0.8	[-3, -2, -1, -2, -1, -2, 0, -1, -1, -1]
+insincere	-1.8	0.6	[-2, -1, -2, -1, -2, -2, -2, -2, -1, -3]
+insincerely	-1.9	0.7	[-2, -1, -2, -2, -1, -3, -2, -3, -1, -2]
+insincerity	-1.4	1.35647	[-1, -1, -3, -2, -1, 2, -2, -1, -2, -3]
+insipid	-2.0	0.7746	[-1, -2, -2, -1, -3, -3, -3, -2, -2, -1]
+inspiration	2.4	0.8	[3, 3, 3, 3, 1, 3, 1, 3, 2, 2]
+inspirational	2.3	0.64031	[2, 3, 2, 3, 2, 3, 2, 3, 1, 2]
+inspirationally	2.3	0.64031	[3, 2, 2, 3, 3, 1, 2, 2, 3, 2]
+inspirations	2.1	0.53852	[2, 2, 2, 2, 1, 2, 2, 3, 3, 2]
+inspirator	1.9	1.22066	[2, 2, 3, 0, 3, 4, 0, 2, 1, 2]
+inspirators	1.2	0.74833	[3, 1, 1, 2, 1, 1, 1, 1, 0, 1]
+inspiratory	1.5	0.67082	[2, 2, 3, 1, 1, 1, 1, 1, 2, 1]
+inspire	2.7	0.78102	[2, 3, 3, 3, 3, 3, 3, 1, 4, 2]
+inspired	2.2	0.87178	[3, 2, 1, 3, 1, 1, 3, 2, 3, 3]
+inspirer	2.2	1.07703	[3, 2, 2, 4, 0, 2, 3, 1, 3, 2]
+inspirers	2.0	0.63246	[2, 2, 3, 2, 3, 2, 1, 2, 1, 2]
+inspires	1.9	1.04403	[2, 2, 2, 4, 0, 2, 3, 1, 1, 2]
+inspiring	1.8	1.07703	[2, 2, 2, -1, 2, 3, 2, 2, 1, 3]
+inspiringly	2.6	0.4899	[2, 3, 3, 2, 3, 3, 2, 3, 2, 3]
+inspirit	1.9	0.7	[1, 3, 2, 1, 2, 1, 3, 2, 2, 2]
+inspirited	1.3	1.18743	[2, 2, 0, 0, 3, 0, 2, 0, 3, 1]
+inspiriting	1.8	0.4	[1, 2, 1, 2, 2, 2, 2, 2, 2, 2]
+inspiritingly	2.1	1.44568	[3, 2, 2, 2, 4, 1, -1, 3, 4, 1]
+inspirits	0.8	1.46969	[3, 0, 3, -2, 0, 1, 1, 0, 2, 0]
+insult	-2.3	1.00499	[-2, -1, -2, -3, -4, -1, -3, -1, -3, -3]
+insulted	-2.3	0.45826	[-2, -2, -2, -2, -3, -2, -2, -2, -3, -3]
+insulter	-2.0	0.63246	[-2, -1, -2, -2, -1, -3, -3, -2, -2, -2]
+insulters	-2.0	0.44721	[-2, -3, -2, -2, -2, -2, -2, -1, -2, -2]
+insulting	-2.2	0.74833	[-3, -2, -3, -3, -2, -3, -1, -2, -2, -1]
+insultingly	-2.3	0.78102	[-3, -3, -1, -2, -2, -3, -2, -1, -3, -3]
+insults	-1.8	0.6	[-2, -3, -2, -2, -1, -1, -1, -2, -2, -2]
+intact	0.8	0.6	[1, 1, 0, 0, 1, 1, 0, 1, 1, 2]
+integrity	1.6	0.66332	[2, 1, 1, 1, 2, 1, 3, 1, 2, 2]
+intellect	2.0	1.09545	[2, 1, 4, 2, 1, 3, 2, 3, 0, 2]
+intellection	0.6	1.0198	[0, 0, 0, 1, 0, 0, 0, 0, 2, 3]
+intellections	0.8	0.87178	[1, 0, 1, 0, 1, 1, 1, 0, 0, 3]
+intellective	1.7	0.78102	[3, 2, 1, 2, 2, 1, 0, 2, 2, 2]
+intellectively	0.8	0.9798	[0, 0, 1, 1, 0, 3, 0, 1, 2, 0]
+intellects	1.8	0.87178	[1, 0, 2, 1, 3, 2, 2, 2, 3, 2]
+intellectual	2.3	0.9	[3, 3, 1, 2, 3, 4, 2, 2, 1, 2]
+intellectualism	2.2	1.07703	[4, 0, 3, 1, 3, 2, 2, 3, 2, 2]
+intellectualist	2.0	1.0	[4, 0, 2, 1, 3, 2, 2, 2, 2, 2]
+intellectualistic	1.3	1.73494	[1, 4, 0, 3, -2, 0, 2, 3, 0, 2]
+intellectualists	0.8	0.74833	[0, 1, 1, 1, 0, 2, 0, 1, 2, 0]
+intellectualities	1.7	1.34536	[3, 3, 0, 2, 1, 0, 0, 4, 2, 2]
+intellectuality	1.7	1.1	[3, 2, 2, 1, 2, 1, 0, 3, 0, 3]
+intellectualization	1.5	1.11803	[2, 1, 2, 1, 4, 2, 0, 0, 2, 1]
+intellectualize	1.5	0.92195	[1, 2, 1, 1, 3, 2, 3, 0, 1, 1]
+intellectualized	1.2	0.74833	[1, 0, 1, 1, 2, 0, 1, 2, 2, 2]
+intellectualizes	1.8	0.87178	[2, 3, 2, 0, 2, 3, 2, 2, 1, 1]
+intellectualizing	0.8	1.77764	[0, 1, 2, 1, 0, 2, 2, -4, 2, 2]
+intellectually	1.4	0.8	[2, 0, 0, 1, 2, 2, 2, 2, 2, 1]
+intellectualness	1.5	0.80623	[2, 2, 2, 2, 0, 0, 1, 2, 2, 2]
+intellectuals	1.6	0.8	[0, 1, 2, 1, 3, 2, 1, 2, 2, 2]
+intelligence	2.1	0.9434	[3, 2, 2, 1, 3, 3, 3, 2, 2, 0]
+intelligencer	1.5	0.80623	[2, 0, 0, 2, 2, 2, 2, 1, 2, 2]
+intelligencers	1.6	0.91652	[2, 2, 0, 2, 2, 0, 3, 2, 2, 1]
+intelligences	1.6	0.91652	[3, 0, 0, 2, 2, 2, 2, 1, 2, 2]
+intelligent	2.0	0.7746	[1, 2, 2, 1, 4, 2, 2, 2, 2, 2]
+intelligential	1.9	0.9434	[3, 2, 2, 1, 3, 2, 2, 3, 0, 1]
+intelligently	2.0	0.63246	[2, 3, 2, 3, 1, 2, 2, 1, 2, 2]
+intelligentsia	1.5	1.20416	[0, 1, 2, 0, 4, 3, 2, 1, 1, 1]
+intelligibility	1.5	0.80623	[2, 2, 0, 2, 2, 1, 2, 0, 2, 2]
+intelligible	1.4	0.8	[1, 2, 2, 1, 0, 2, 1, 1, 3, 1]
+intelligibleness	1.5	1.20416	[2, 1, 3, -1, 2, 2, 2, 0, 1, 3]
+intelligibly	1.2	0.87178	[1, 2, 1, 2, 1, -1, 2, 2, 1, 1]
+intense	0.3	0.45826	[0, 1, 1, 0, 0, 0, 0, 0, 1, 0]
+interest	2.0	1.18322	[2, 3, 3, 1, 1, 3, 4, 1, 2, 0]
+interested	1.7	0.45826	[2, 1, 2, 2, 1, 2, 2, 2, 1, 2]
+interestedly	1.5	0.67082	[2, 2, 2, 1, 2, 1, 2, 1, 0, 2]
+interesting	1.7	0.78102	[1, 2, 1, 3, 1, 1, 1, 3, 2, 2]
+interestingly	1.7	0.45826	[2, 2, 2, 1, 2, 1, 1, 2, 2, 2]
+interestingness	1.8	0.87178	[2, 3, 1, 3, 1, 3, 2, 1, 1, 1]
+interests	1.0	0.89443	[1, 0, 1, 2, 0, 0, 1, 1, 1, 3]
+interrogated	-1.6	1.0198	[-3, -1, -1, -1, -2, -1, -3, -1, -3, 0]
+interrupt	-1.4	0.4899	[-2, -1, -1, -1, -2, -2, -1, -1, -2, -1]
+interrupted	-1.2	0.6	[-1, -2, -1, 0, -1, -1, -2, -1, -2, -1]
+interrupter	-1.1	0.53852	[-1, -2, -1, 0, -1, -1, -1, -1, -2, -1]
+interrupters	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -1, -2, -1]
+interruptible	-1.3	1.00499	[-2, -1, 0, -2, 0, -3, -2, -1, 0, -2]
+interrupting	-1.2	0.4	[-2, -1, -1, -1, -1, -2, -1, -1, -1, -1]
+interruption	-1.5	0.67082	[-1, -1, -2, -3, -2, -1, -1, -1, -2, -1]
+interruptions	-1.7	0.45826	[-2, -2, -2, -2, -2, -1, -1, -1, -2, -2]
+interruptive	-1.4	0.66332	[-2, -2, -1, -2, -2, 0, -1, -1, -1, -2]
+interruptor	-1.3	0.64031	[-2, -1, -1, -1, 0, -2, -2, -2, -1, -1]
+interrupts	-1.3	0.64031	[-1, -1, -2, -1, -1, -1, -1, -1, -3, -1]
+intimidate	-0.8	1.46969	[-1, -2, -2, -2, -2, -1, 2, 1, 1, -2]
+intimidated	-1.9	0.7	[-2, -1, -3, -3, -1, -2, -2, -1, -2, -2]
+intimidates	-1.3	0.78102	[-2, -1, -1, -1, -3, -2, -1, -1, -1, 0]
+intimidating	-1.9	1.04403	[0, -2, -1, -3, -2, -1, -1, -3, -3, -3]
+intimidatingly	-1.1	1.64012	[2, -2, -3, -1, -2, -2, 2, -2, -1, -2]
+intimidation	-1.8	1.249	[1, -2, -3, -1, -2, -3, -1, -3, -1, -3]
+intimidations	-1.4	1.49666	[1, -2, -2, -2, -1, -1, -1, -4, 1, -3]
+intimidator	-1.6	0.4899	[-1, -1, -2, -2, -1, -2, -2, -1, -2, -2]
+intimidators	-1.6	0.8	[-1, -1, -3, -2, -1, -1, -3, -1, -2, -1]
+intimidatory	-1.1	1.22066	[-1, -2, -3, -1, -1, -1, -2, 2, -1, -1]
+intricate	0.6	0.66332	[1, 0, 2, 1, 0, 1, 1, 0, 0, 0]
+intrigues	0.9	0.9434	[2, -1, 2, 1, 2, 0, 1, 1, 0, 1]
+invigorate	1.9	0.83066	[2, 2, 2, 0, 2, 3, 3, 2, 1, 2]
+invigorated	0.8	1.8868	[-2, 3, 2, 2, -2, -2, 2, 2, 1, 2]
+invigorates	2.1	0.53852	[3, 2, 3, 2, 1, 2, 2, 2, 2, 2]
+invigorating	2.1	0.7	[2, 1, 1, 3, 3, 3, 2, 2, 2, 2]
+invigoratingly	2.0	0.63246	[2, 2, 1, 2, 1, 3, 2, 2, 2, 3]
+invigoration	1.5	1.36015	[2, 2, 1, -2, 1, 3, 3, 2, 1, 2]
+invigorations	1.2	0.87178	[1, -1, 2, 2, 1, 1, 2, 1, 2, 1]
+invigorator	1.1	1.3	[3, 1, 0, 2, 2, -2, 1, 1, 2, 1]
+invigorators	1.2	0.87178	[1, 1, 1, 1, 3, 2, 0, 0, 1, 2]
+invincible	2.2	1.77764	[4, 1, 3, 2, 4, 1, 4, -1, 0, 4]
+invite	0.6	0.66332	[2, 1, 1, 0, 0, 0, 0, 1, 1, 0]
+inviting	1.3	0.45826	[1, 1, 1, 2, 1, 2, 2, 1, 1, 1]
+invulnerable	1.3	1.73494	[2, 3, 4, 2, 0, 3, 0, 1, -2, 0]
+irate	-2.9	0.53852	[-3, -3, -3, -2, -3, -4, -3, -3, -2, -3]
+ironic	-0.5	1.28452	[1, 0, 0, 0, 0, 0, -4, -1, -1, 0]
+irony	-0.2	1.07703	[-1, 0, -3, 0, 0, 0, 1, 0, 1, 0]
+irrational	-1.4	0.4899	[-1, -1, -1, -2, -2, -2, -1, -1, -2, -1]
+irrationalism	-1.5	0.5	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -2]
+irrationalist	-2.1	0.9434	[-1, -4, -2, -2, -3, -3, -2, -1, -1, -2]
+irrationalists	-1.5	0.92195	[-2, -2, -1, -2, -2, 1, -1, -2, -2, -2]
+irrationalities	-1.5	0.80623	[-2, -2, 0, -1, -1, -1, -2, -3, -1, -2]
+irrationality	-1.7	0.9	[-3, -3, -1, -2, -1, -1, -1, -1, -3, -1]
+irrationally	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -2]
+irrationals	-1.1	0.83066	[-2, 0, -1, 0, -1, -1, -3, -1, -1, -1]
+irresistible	1.4	2.2	[2, 3, 2, 3, 4, 4, 1, -1, -2, -2]
+irresolute	-1.4	0.66332	[-2, -2, -1, -2, -1, -1, -1, -2, -2, 0]
+irresponsible	-1.9	0.3	[-2, -2, -2, -2, -2, -2, -1, -2, -2, -2]
+irreversible	-0.8	0.87178	[-2, -2, 0, -1, 0, 0, 0, -1, -2, 0]
+irritabilities	-1.7	0.64031	[-2, -2, -2, -1, -1, -1, -1, -2, -3, -2]
+irritability	-1.4	1.28062	[-2, -1, -2, -1, 2, -2, -2, -2, -1, -3]
+irritable	-2.1	0.7	[-2, -2, -3, -1, -2, -1, -3, -2, -3, -2]
+irritableness	-1.7	0.64031	[-2, -2, -2, -1, -2, -1, -1, -3, -1, -2]
+irritably	-1.8	0.6	[-2, -2, -1, -1, -3, -2, -1, -2, -2, -2]
+irritant	-2.3	0.78102	[-3, -3, -3, -3, -3, -1, -2, -2, -2, -1]
+irritants	-2.1	0.83066	[-2, -3, -1, -4, -2, -1, -2, -2, -2, -2]
+irritate	-1.8	0.6	[-3, -2, -2, -2, -1, -2, -1, -2, -1, -2]
+irritated	-2.0	0.63246	[-1, -2, -2, -2, -3, -2, -2, -3, -1, -2]
+irritates	-1.7	0.78102	[-1, -2, -1, -1, -3, -2, -2, -3, -1, -1]
+irritating	-2.0	0.63246	[-2, -2, -2, -1, -1, -3, -2, -2, -3, -2]
+irritatingly	-2.0	0.44721	[-2, -2, -2, -3, -1, -2, -2, -2, -2, -2]
+irritation	-2.3	0.78102	[-3, -2, -2, -2, -1, -3, -3, -1, -3, -3]
+irritations	-1.5	0.67082	[-2, -2, -1, -1, -1, -1, -1, -2, -3, -1]
+irritative	-2.0	0.63246	[-3, -2, -3, -2, -1, -2, -2, -2, -1, -2]
+isolatable	0.2	1.249	[1, 0, -2, 0, -1, -1, 2, 0, 2, 1]
+isolate	-0.8	0.74833	[-1, -1, -1, 0, 0, 0, 0, -2, -1, -2]
+isolated	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -2, -1, -3, -1]
+isolates	-1.3	0.64031	[-1, -1, -1, -1, -2, -1, -3, -1, -1, -1]
+isolation	-1.7	0.78102	[-1, -3, -1, -2, -2, -1, -3, -1, -2, -1]
+isolationism	0.4	1.62481	[2, 0, -1, -2, -1, 3, 0, 2, -1, 2]
+isolationist	0.7	1.55242	[2, 0, 0, -1, -1, 3, 0, 2, -1, 3]
+isolations	-0.5	1.11803	[-1, -2, -2, -1, 1, 1, -1, 0, 1, -1]
+isolator	-0.4	0.66332	[0, 0, -1, 0, -1, 0, -2, 0, 0, 0]
+isolators	-0.4	1.42829	[-2, -1, -1, -2, 2, 2, -1, 1, -1, -1]
+itchy	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -1, -2, -1]
+jackass	-1.8	1.07703	[-1, 0, -3, -2, -2, -3, 0, -2, -2, -3]
+jackasses	-2.8	0.9798	[-2, -2, -4, -3, -4, -4, -3, -1, -2, -3]
+jaded	-1.6	0.66332	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -3]
+jailed	-2.2	0.87178	[-4, -3, -2, -2, -1, -2, -2, -3, -1, -2]
+jaunty	1.2	0.6	[2, 1, 0, 2, 1, 1, 1, 2, 1, 1]
+jealous	-2.0	0.63246	[-2, -2, -3, -2, -3, -2, -1, -1, -2, -2]
+jealousies	-2.0	0.63246	[-2, -3, -2, -1, -2, -3, -2, -1, -2, -2]
+jealously	-2.0	0.89443	[-1, -3, -1, -4, -2, -2, -1, -2, -2, -2]
+jealousness	-1.7	0.45826	[-1, -2, -2, -2, -2, -1, -1, -2, -2, -2]
+jealousy	-1.3	1.73494	[-2, -3, -2, -2, -2, 2, -3, -1, 2, -2]
+jeopardy	-2.1	0.9434	[-3, -3, -3, -1, -1, -3, -2, -1, -1, -3]
+jerk	-1.4	0.8	[-1, -1, -1, -2, -3, 0, -2, -1, -1, -2]
+jerked	-0.8	0.74833	[0, -1, -1, 0, -2, -1, 0, -1, 0, -2]
+jerks	-1.1	1.51327	[-2, -2, -1, -2, -1, 0, -2, 3, -2, -2]
+jewel	1.5	1.20416	[1, 3, 2, 0, 2, 1, 3, 0, 3, 0]
+jewels	2.0	1.34164	[3, 1, 0, 0, 4, 3, 3, 2, 3, 1]
+jocular	1.2	1.249	[0, 1, 2, -2, 1, 2, 2, 2, 2, 2]
+join	1.2	0.74833	[2, 2, 1, 2, 1, 0, 1, 2, 0, 1]
+joke	1.2	0.74833	[1, 1, 1, 1, 1, 1, 0, 2, 1, 3]
+joked	1.3	0.64031	[1, 1, 2, 2, 0, 2, 1, 1, 2, 1]
+joker	0.5	0.92195	[1, 1, -1, 1, 2, -1, 1, 1, 0, 0]
+jokes	1.0	0.7746	[1, 1, -1, 1, 1, 2, 1, 1, 2, 1]
+jokester	1.5	0.67082	[2, 2, 2, 2, 1, 1, 0, 1, 2, 2]
+jokesters	0.9	0.83066	[0, 0, 2, 1, 1, 2, 2, 0, 1, 0]
+jokey	1.1	0.3	[1, 1, 2, 1, 1, 1, 1, 1, 1, 1]
+joking	0.9	0.53852	[1, 2, 1, 1, 1, 0, 1, 1, 0, 1]
+jollied	2.4	0.66332	[3, 3, 2, 2, 3, 3, 2, 2, 1, 3]
+jollier	2.4	0.4899	[2, 2, 3, 3, 2, 2, 2, 3, 2, 3]
+jollies	2.0	0.63246	[1, 2, 3, 2, 2, 2, 1, 2, 2, 3]
+jolliest	2.9	0.7	[3, 3, 2, 4, 3, 2, 3, 4, 2, 3]
+jollification	2.2	0.74833	[2, 3, 3, 1, 2, 1, 3, 2, 3, 2]
+jollifications	2.0	0.7746	[2, 3, 2, 2, 2, 2, 3, 2, 0, 2]
+jollify	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 3, 1, 2]
+jollily	2.7	0.64031	[3, 3, 3, 3, 3, 3, 3, 1, 3, 2]
+jolliness	2.5	0.67082	[3, 1, 2, 3, 2, 3, 3, 3, 2, 3]
+jollities	1.7	0.64031	[2, 1, 2, 2, 1, 2, 2, 3, 1, 1]
+jollity	1.8	1.6	[3, 2, 1, 1, 4, 3, 1, 2, 3, -2]
+jolly	2.3	1.00499	[4, 3, 3, 1, 1, 1, 3, 2, 3, 2]
+jollying	2.3	0.64031	[2, 3, 3, 1, 3, 3, 2, 2, 2, 2]
+jovial	1.9	0.53852	[2, 2, 1, 2, 1, 2, 3, 2, 2, 2]
+joy	2.8	0.74833	[3, 2, 3, 4, 3, 3, 3, 1, 3, 3]
+joyance	2.3	0.9	[1, 3, 4, 2, 2, 1, 2, 3, 2, 3]
+joyed	2.9	0.3	[3, 3, 3, 3, 3, 3, 3, 2, 3, 3]
+joyful	2.9	0.53852	[3, 2, 3, 3, 2, 3, 4, 3, 3, 3]
+joyfuller	2.4	0.66332	[2, 4, 3, 2, 2, 2, 3, 2, 2, 2]
+joyfully	2.5	0.67082	[2, 2, 3, 3, 2, 2, 3, 4, 2, 2]
+joyfulness	2.7	1.00499	[4, 3, 1, 3, 3, 3, 4, 2, 1, 3]
+joying	2.5	0.67082	[2, 2, 1, 3, 3, 3, 3, 3, 3, 2]
+joyless	-2.5	0.67082	[-1, -2, -3, -3, -3, -3, -2, -2, -3, -3]
+joylessly	-1.7	1.1	[-2, -2, -3, -3, -2, -1, 1, -2, -1, -2]
+joylessness	-2.7	0.9	[-4, -3, -3, -3, -3, -3, -3, -1, -1, -3]
+joyous	3.1	0.7	[3, 4, 3, 2, 4, 3, 3, 4, 2, 3]
+joyously	2.9	0.7	[2, 3, 4, 3, 4, 2, 2, 3, 3, 3]
+joyousness	2.8	0.74833	[3, 3, 1, 3, 3, 3, 4, 2, 3, 3]
+joypop	-0.2	1.93907	[-3, 1, 2, 2, -3, -1, -2, -1, 1, 2]
+joypoppers	-0.1	1.22066	[2, -1, 1, -1, -1, 1, 1, 0, -2, -1]
+joyridden	0.6	1.8	[-2, -1, 4, 0, 0, 2, 1, -1, 0, 3]
+joyride	1.1	1.22066	[-1, 1, 2, 0, 2, 0, 2, 2, 3, 0]
+joyrider	0.7	1.26886	[2, -2, 1, 2, 0, 2, -1, 1, 1, 1]
+joyriders	1.3	1.18743	[1, 0, 0, 1, 4, 3, 1, 1, 1, 1]
+joyrides	0.8	1.32665	[2, -2, 1, 2, 0, 2, -1, 1, 2, 1]
+joyriding	0.9	1.04403	[1, -1, 1, 1, 0, 2, 0, 1, 3, 1]
+joyrode	1.0	1.48324	[4, 0, -2, 0, 2, 1, 2, 1, 1, 1]
+joys	2.2	0.4	[2, 2, 2, 2, 2, 3, 2, 3, 2, 2]
+joystick	0.7	0.78102	[1, 0, 2, 2, 0, 0, 1, 1, 0, 0]
+joysticks	0.2	0.4	[0, 0, 0, 0, 1, 0, 0, 1, 0, 0]
+jubilant	3.0	0.63246	[3, 3, 4, 3, 3, 2, 3, 4, 2, 3]
+jumpy	-1.0	0.63246	[0, 0, -2, -1, -1, -1, -1, -1, -2, -1]
+justice	2.4	1.0198	[3, 2, 1, 2, 3, 2, 4, 4, 2, 1]
+justifiably	1.0	0.7746	[0, 1, 0, 1, 1, 1, 0, 2, 2, 2]
+justified	1.7	0.64031	[1, 2, 2, 3, 1, 1, 1, 2, 2, 2]
+keen	1.5	0.67082	[1, 1, 3, 1, 2, 1, 1, 2, 2, 1]
+keened	0.3	1.00499	[-2, 0, 1, 0, 1, 1, 0, 2, 0, 0]
+keener	0.5	1.20416	[-1, -1, 0, -1, 2, 1, 2, 2, 1, 0]
+keeners	0.6	0.4899	[1, 0, 0, 1, 1, 0, 1, 1, 0, 1]
+keenest	1.9	0.83066	[3, 3, 1, 1, 3, 2, 2, 1, 2, 1]
+keening	-0.7	1.41774	[0, -3, -1, -1, -3, 1, -1, 1, 1, -1]
+keenly	1.0	0.7746	[2, 1, 1, 0, 1, 0, 2, 1, 2, 0]
+keenness	1.4	0.4899	[1, 1, 2, 2, 1, 1, 1, 2, 2, 1]
+keens	0.1	1.22066	[1, -3, 0, 0, 0, 2, 1, 0, 0, 0]
+kewl	1.3	0.45826	[2, 1, 1, 1, 2, 1, 2, 1, 1, 1]
+kidding	0.4	0.8	[0, 1, 0, -1, 1, 1, 1, 1, -1, 1]
+kill	-3.7	0.45826	[-4, -4, -4, -4, -3, -4, -4, -4, -3, -3]
+killdeer	-1.1	1.04403	[-3, 0, 0, -1, -2, 0, -1, -2, -2, 0]
+killdeers	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
+killdees	-0.6	0.66332	[-2, 0, 0, 0, -1, 0, -1, -1, -1, 0]
+killed	-3.5	0.67082	[-3, -3, -2, -4, -4, -4, -3, -4, -4, -4]
+killer	-3.3	0.64031	[-4, -4, -3, -3, -4, -4, -3, -3, -2, -3]
+killers	-3.3	0.45826	[-3, -3, -4, -3, -3, -3, -4, -3, -4, -3]
+killick	0.1	0.3	[0, 1, 0, 0, 0, 0, 0, 0, 0, 0]
+killie	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
+killifish	-0.1	0.7	[0, 0, 0, 0, -2, 0, 0, 0, 1, 0]
+killifishes	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
+killing	-3.4	1.2	[-4, 0, -4, -4, -4, -3, -4, -3, -4, -4]
+killingly	-2.6	1.0198	[-3, -2, -4, -2, -1, -3, -4, -3, -3, -1]
+killings	-3.5	0.67082	[-4, -3, -4, -4, -2, -3, -4, -4, -3, -4]
+killjoy	-2.1	0.83066	[-1, -2, -3, -2, -1, -3, -2, -1, -3, -3]
+killjoys	-1.7	0.9	[-1, -3, -3, -1, -2, -1, -2, 0, -2, -2]
+killock	-0.3	0.64031	[0, 0, 0, 0, -2, 0, 0, 0, -1, 0]
+killocks	-0.4	0.66332	[0, 0, 0, -2, -1, 0, -1, 0, 0, 0]
+kills	-2.5	0.92195	[-2, -3, -2, -3, -4, -1, -3, -3, -1, -3]
+kind	2.4	0.66332	[2, 2, 3, 3, 2, 3, 3, 2, 1, 3]
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+kindness	2.0	0.63246	[2, 1, 3, 3, 2, 1, 2, 2, 2, 2]
+kindnesses	2.3	0.64031	[3, 1, 3, 2, 3, 2, 3, 2, 2, 2]
+kiss	1.8	1.6	[4, 0, 3, 3, 2, 0, 4, 2, 0, 0]
+kissable	2.0	0.89443	[2, 2, 2, 2, 4, 2, 3, 1, 1, 1]
+kissably	1.9	1.04403	[1, 3, 4, 1, 2, 1, 3, 2, 1, 1]
+kissed	1.6	1.11355	[2, 4, 1, 1, 1, 2, 3, 0, 1, 1]
+kisser	1.7	1.34536	[2, 4, 1, 2, -1, 2, 3, 0, 2, 2]
+kissers	1.5	0.80623	[1, 1, 1, 0, 2, 2, 3, 2, 1, 2]
+kisses	2.3	0.9	[2, 4, 2, 2, 1, 2, 4, 2, 2, 2]
+kissing	2.7	0.78102	[3, 3, 4, 1, 3, 2, 2, 3, 3, 3]
+kissy	1.8	0.6	[2, 2, 2, 3, 1, 1, 2, 2, 1, 2]
+kudos	2.3	0.64031	[2, 4, 2, 3, 2, 2, 2, 2, 2, 2]
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+lackadaisical	-1.6	0.66332	[-1, -1, -2, -1, -2, -2, -3, -1, -2, -1]
+lag	-1.4	0.66332	[-1, -1, -1, -1, -1, -3, -1, -2, -2, -1]
+lagged	-1.2	0.6	[-2, -2, -1, -2, -1, -1, 0, -1, -1, -1]
+lagging	-1.1	0.83066	[-2, -2, -2, -1, 0, 0, -1, 0, -1, -2]
+lags	-1.5	0.67082	[-2, -1, -1, -2, -1, -3, -1, -2, -1, -1]
+laidback	0.5	1.28452	[1, -1, 1, -2, -1, 1, 2, 1, 1, 2]
+lame	-1.8	0.74833	[-1, -3, -1, -2, -2, -1, -2, -3, -1, -2]
+lamebrain	-1.6	0.91652	[-3, -2, -1, 0, -3, -1, -1, -2, -2, -1]
+lamebrained	-2.5	0.67082	[-3, -3, -2, -2, -2, -2, -4, -3, -2, -2]
+lamebrains	-1.2	1.46969	[-2, -1, -3, -1, 2, -2, 1, -2, -2, -2]
+lamedh	0.1	0.53852	[0, 0, 0, 0, 0, 1, 1, -1, 0, 0]
+lamella	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
+lamellae	-0.1	0.3	[0, 0, 0, 0, 0, 0, -1, 0, 0, 0]
+lamellas	0.1	0.53852	[0, 0, 0, 0, 0, 1, 0, 1, 0, -1]
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+lamellibranchs	-0.1	0.3	[0, 0, -1, 0, 0, 0, 0, 0, 0, 0]
+lamely	-2.0	0.89443	[-2, -3, 0, -1, -2, -3, -2, -3, -2, -2]
+lameness	-0.8	1.07703	[-2, -2, -1, -1, -1, 0, 2, -1, -1, -1]
+lament	-2.0	1.26491	[-3, -3, 1, -1, -2, -2, -1, -3, -3, -3]
+lamentable	-1.5	1.0247	[-2, 0, -2, -1, 0, -2, -3, -1, -1, -3]
+lamentableness	-1.3	0.64031	[-2, -1, -1, 0, -2, -1, -1, -1, -2, -2]
+lamentably	-1.5	0.80623	[-2, 0, -3, -1, -1, -2, -2, -1, -1, -2]
+lamentation	-1.4	1.49666	[-3, -2, 0, -3, -1, -1, 2, -2, -1, -3]
+lamentations	-1.9	1.44568	[-2, -2, -2, -3, 2, -1, -3, -3, -2, -3]
+lamented	-1.4	0.91652	[-1, 0, -1, -2, -2, -1, -2, -3, -2, 0]
+lamenter	-1.2	0.87178	[-1, 0, -1, -1, -1, -1, -2, -3, -2, 0]
+lamenters	-0.5	0.67082	[-1, 0, 0, -1, -1, 0, 0, 0, -2, 0]
+lamenting	-2.0	1.09545	[0, -2, -1, -4, -1, -3, -2, -2, -3, -2]
+laments	-1.5	0.80623	[-1, -3, 0, -1, -2, -1, -2, -2, -2, -1]
+lamer	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -1, -2, -2, -1]
+lames	-1.2	0.6	[-2, -1, -1, -2, 0, -1, -1, -2, -1, -1]
+lamest	-1.5	1.28452	[-3, -2, -1, -4, 1, -1, -1, -1, -1, -2]
+landmark	0.3	0.64031	[2, 0, 0, 0, 0, 0, 0, 0, 1, 0]
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+laughable	0.2	1.72047	[-2, -1, 3, -1, 2, 2, -1, -1, -1, 2]
+laughableness	1.2	1.6	[2, 0, 3, 2, 2, 1, 3, -2, 2, -1]
+laughably	1.2	1.249	[2, 1, 2, 1, 1, 1, 2, 3, -2, 1]
+laughed	2.0	0.63246	[2, 2, 3, 1, 2, 1, 2, 2, 3, 2]
+laugher	1.7	0.45826	[2, 2, 1, 1, 2, 1, 2, 2, 2, 2]
+laughers	1.7	0.9	[1, 2, 4, 1, 2, 1, 2, 1, 1, 2]
+laughing	2.2	0.87178	[2, 4, 1, 1, 3, 2, 2, 2, 2, 3]
+laughingly	2.3	1.1	[2, 4, 0, 2, 3, 1, 3, 2, 3, 3]
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+laughs	2.2	0.6	[1, 2, 2, 3, 3, 2, 3, 2, 2, 2]
+laughter	2.2	0.6	[2, 3, 2, 2, 2, 2, 3, 1, 3, 2]
+laughters	2.2	0.6	[3, 1, 2, 2, 2, 3, 3, 2, 2, 2]
+launched	0.5	0.80623	[2, 0, 0, 0, 0, 0, 0, 1, 2, 0]
+lawl	1.4	1.42829	[0, 2, 2, 1, 3, -2, 3, 1, 2, 2]
+lawsuit	-0.9	1.22066	[-2, -2, -1, -3, -1, 1, 0, 1, -1, -1]
+lawsuits	-0.6	1.68523	[-2, -1, 0, 3, 2, -1, -1, -2, -2, -2]
+lazier	-2.3	0.64031	[-3, -2, -3, -2, -1, -2, -2, -3, -2, -3]
+laziest	-2.7	0.64031	[-2, -2, -3, -4, -3, -3, -2, -2, -3, -3]
+lazy	-1.5	1.36015	[-3, -1, -3, -2, 2, -1, -1, -2, -2, -2]
+leak	-1.4	0.66332	[-1, -2, -1, -1, -1, -1, -1, -2, -3, -1]
+leaked	-1.3	0.78102	[-2, -2, -1, -3, -1, 0, -1, -1, -1, -1]
+leave	-0.2	0.9798	[1, -1, -1, 0, 0, -1, 2, -1, 0, -1]
+leet	1.3	1.48661	[2, 4, 2, 2, 0, 1, -2, 2, 1, 1]
+legal	0.5	0.80623	[0, 0, 0, 2, 0, 1, 0, 0, 2, 0]
+legally	0.4	0.8	[1, 0, 0, 0, 1, 0, 2, 1, 0, -1]
+lenient	1.1	1.04403	[1, 3, 1, 2, 1, 1, 2, -1, 0, 1]
+lethargic	-1.2	0.74833	[-2, -1, -2, -2, 0, -1, -1, -2, 0, -1]
+lethargy	-1.4	0.91652	[-1, 0, -2, -1, -2, 0, -2, -1, -3, -2]
+liabilities	-0.8	0.9798	[-1, 2, -1, -1, -1, -1, -1, -1, -2, -1]
+liability	-0.8	1.83303	[-2, -3, -1, -1, 3, -3, -1, -1, 2, -1]
+liar	-2.3	0.78102	[-1, -2, -3, -3, -2, -2, -3, -1, -3, -3]
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+liars	-2.4	0.66332	[-3, -2, -2, -3, -2, -1, -3, -3, -2, -3]
+libelous	-2.1	1.3	[-3, -1, -1, -2, 1, -3, -3, -3, -3, -3]
+libertarian	0.9	0.9434	[1, 2, 0, 1, 0, 0, 0, 3, 1, 1]
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+libertarians	0.1	0.83066	[0, 0, 1, 0, 0, -1, -1, 0, 2, 0]
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+libertine	-0.9	1.44568	[0, -1, 0, 0, -1, -3, 2, -2, -1, -3]
+libertines	0.4	1.35647	[-1, 3, -1, -1, 1, 1, 1, 2, 0, -1]
+libertinisms	1.2	1.249	[0, 0, 3, 1, 1, 1, 4, 0, 1, 1]
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+lied	-1.6	1.2	[-3, 0, -3, 1, -2, -1, -2, -2, -2, -2]
+lies	-1.8	0.9798	[-1, -1, -1, 0, -2, -3, -3, -2, -3, -2]
+lifesaver	2.8	0.74833	[3, 3, 4, 2, 3, 1, 3, 3, 3, 3]
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+likeable	2.0	0.63246	[1, 3, 2, 2, 2, 3, 2, 1, 2, 2]
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+liking	1.7	0.78102	[3, 1, 2, 1, 1, 2, 3, 1, 2, 1]
+limitation	-1.2	0.6	[-2, -1, 0, -1, -1, -2, -1, -2, -1, -1]
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+livelier	1.7	0.78102	[2, 2, 1, 3, 1, 3, 2, 1, 1, 1]
+liveliest	2.1	0.9434	[2, 1, 2, 3, 1, 1, 2, 4, 3, 2]
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+livelihoods	0.9	1.13578	[0, 0, 0, 3, 2, 2, 0, 2, 0, 0]
+livelily	1.8	0.6	[2, 2, 2, 3, 1, 2, 1, 2, 2, 1]
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+loathed	-2.1	1.44568	[-4, -3, -3, -3, -1, 1, -1, -1, -3, -3]
+loathes	-1.9	1.13578	[-1, -4, -1, -3, -3, -1, -1, -3, -1, -1]
+loathing	-2.7	0.78102	[-3, -3, -3, -1, -4, -2, -3, -3, -2, -3]
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+lobbying	-0.3	0.45826	[0, -1, 0, 0, 0, 0, 0, -1, -1, 0]
+lol	1.8	1.46969	[1, 3, 4, 1, 2, 4, 1, 2, -1, 1]
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+lonelier	-1.4	0.66332	[-2, -1, -2, -2, 0, -2, -1, -1, -1, -2]
+loneliest	-2.4	0.8	[-3, -1, -2, -4, -2, -2, -3, -3, -2, -2]
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+lonelinesses	-1.5	1.36015	[-2, -2, -1, -1, 2, -1, -3, -2, -3, -2]
+lonely	-1.5	0.5	[-1, -2, -2, -1, -1, -1, -1, -2, -2, -2]
+loneness	-1.1	0.83066	[-1, -2, -1, -2, -1, -1, -2, 1, -1, -1]
+loner	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -2, -2, -1]
+loners	-0.9	0.53852	[-1, -1, -2, -1, -1, -1, 0, 0, -1, -1]
+lonesome	-1.5	0.67082	[-2, -1, -2, -1, -2, -1, -2, 0, -2, -2]
+lonesomely	-1.3	1.00499	[-2, -2, -2, -2, -1, -2, 0, -2, -1, 1]
+lonesomeness	-1.8	0.6	[-2, -2, -1, -3, -1, -2, -2, -2, -1, -2]
+lonesomes	-1.4	0.4899	[-2, -1, -1, -1, -1, -1, -2, -2, -2, -1]
+longing	-0.1	0.9434	[0, -1, 0, -1, -1, 0, 2, -1, 1, 0]
+longingly	0.7	0.45826	[1, 0, 1, 0, 1, 1, 1, 0, 1, 1]
+longings	0.4	1.2	[2, 0, -1, -1, 0, 1, 3, 0, 0, 0]
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+loomed	-1.1	1.04403	[-2, -2, -1, -1, -1, -1, 0, -1, -3, 1]
+looming	-0.5	1.5	[-2, -1, -1, 0, -2, -2, 3, -1, 0, 1]
+looms	-0.6	1.0198	[-1, -2, -1, -1, 0, 0, 1, -2, 1, -1]
+loose	-1.3	1.18743	[-2, -1, 0, -2, 0, -1, 0, -2, -4, -1]
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+lose	-1.7	0.45826	[-1, -2, -1, -2, -1, -2, -2, -2, -2, -2]
+loser	-2.4	0.66332	[-3, -2, -2, -2, -2, -3, -3, -1, -3, -3]
+losers	-2.4	0.8	[-3, -1, -2, -2, -4, -2, -3, -3, -2, -2]
+loses	-1.3	1.00499	[0, -1, -1, -1, -1, -4, -1, -1, -2, -1]
+losing	-1.6	0.8	[-1, -1, -1, -2, -1, -2, -3, -3, -1, -1]
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+losses	-1.7	0.9	[-2, -1, -2, -3, 0, -1, -3, -1, -2, -2]
+lossy	-1.2	0.87178	[-2, -2, -1, -2, 0, 0, 0, -1, -2, -2]
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+loused	-1.0	0.7746	[-1, -1, -1, -1, 0, 0, -2, 0, -2, -2]
+louses	-1.3	0.78102	[-2, -1, -2, -1, -1, 0, -2, 0, -2, -2]
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+lousiest	-2.6	0.8	[-4, -2, -3, -3, -1, -2, -3, -3, -2, -3]
+lousily	-1.2	0.9798	[-1, -1, -2, -2, -2, -2, 0, -1, 1, -2]
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+loving	2.9	0.53852	[3, 2, 3, 3, 3, 2, 4, 3, 3, 3]
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+lowing	-0.5	0.67082	[0, 0, 0, -1, 0, 0, -1, -2, -1, 0]
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+lowlifes	-2.2	1.249	[-3, -2, -3, -4, -2, 1, -2, -3, -2, -2]
+lowlight	-2.0	1.26491	[-3, -2, -1, -3, 1, -2, -1, -3, -3, -3]
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+lowlinesses	-1.2	1.07703	[-3, -1, -2, -2, 0, -1, -1, -1, -2, 1]
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+lucky	1.8	0.74833	[2, 1, 1, 1, 3, 2, 1, 2, 2, 3]
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+ludicrously	-0.2	1.83303	[3, -1, 0, -2, -1, 0, 3, -3, -1, 0]
+ludicrousness	-1.9	1.57797	[-1, 2, -2, -3, -2, -2, -3, -4, -1, -3]
+lugubrious	-2.1	1.37477	[-3, -2, -3, -3, -3, 1, -2, -3, 0, -3]
+lulz	2.0	1.0	[2, 2, 2, 3, 4, 1, 3, 1, 1, 1]
+lunatic	-2.2	1.32665	[-2, -3, -4, -2, -3, -2, -1, -3, 1, -3]
+lunatics	-1.6	1.95959	[-4, -2, -3, -4, -2, 2, -1, -3, 1, 0]
+lurk	-0.8	0.87178	[-1, -1, 0, -3, -1, 0, -1, 0, -1, 0]
+lurking	-0.5	1.11803	[1, -1, -1, 0, -1, -2, 1, -2, 1, -1]
+lurks	-0.9	1.04403	[-1, -1, -1, -2, -2, -1, -1, -1, 2, -1]
+lying	-2.4	0.8	[-2, -4, -3, -1, -2, -2, -3, -2, -2, -3]
+mad	-2.2	0.74833	[-3, -3, -1, -1, -2, -3, -2, -2, -3, -2]
+maddening	-2.2	0.74833	[-3, -3, -1, -1, -3, -2, -2, -3, -2, -2]
+madder	-1.2	1.16619	[-2, 0, -3, 0, 0, -1, -3, -1, -2, 0]
+maddest	-2.8	1.16619	[-4, -4, -4, -4, -1, -3, -2, -1, -2, -3]
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+magnificently	3.4	0.66332	[3, 3, 3, 4, 4, 2, 4, 4, 3, 4]
+magnifico	1.8	0.87178	[2, 1, 1, 2, 1, 1, 3, 3, 3, 1]
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+maniacally	-1.7	0.78102	[-1, -2, -1, -2, -3, -2, -1, -3, -1, -1]
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+manipulated	-1.6	0.4899	[-2, -1, -1, -2, -1, -2, -2, -1, -2, -2]
+manipulating	-1.5	0.80623	[-1, -1, -1, -2, -2, -1, -2, -2, -3, 0]
+manipulation	-1.2	1.72047	[2, -3, -2, -3, -1, -1, -2, 2, -2, -2]
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+masochism	-1.6	1.11355	[-1, 0, -2, -2, -2, -2, 0, -4, -1, -2]
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+masochist	-1.7	0.9	[-1, 0, -3, -1, -2, -2, -2, -2, -1, -3]
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+masochistically	-1.6	1.35647	[-1, -1, -3, -3, -3, -3, 0, -2, 1, -1]
+masochists	-1.2	1.07703	[1, -2, 0, -2, -3, -1, -2, -1, -1, -1]
+masterpiece	3.1	0.83066	[3, 4, 4, 4, 2, 2, 2, 4, 3, 3]
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+melancholic	-0.3	1.18743	[0, 2, -2, 0, 1, -1, 0, -2, 0, -1]
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+melancholy	-1.9	1.13578	[-3, -2, -3, -2, -3, -2, -2, 1, -1, -2]
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+meriting	1.1	1.13578	[1, 2, 1, -2, 1, 1, 2, 2, 1, 2]
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+opportunistic	-0.1	2.11896	[-2, 1, -1, 0, -4, 2, -1, 4, 1, -1]
+opportunistically	0.9	1.51327	[1, -3, 1, 3, 2, 2, 1, 0, 1, 1]
+opportunists	0.3	1.34536	[0, -1, -1, 2, 1, 3, -1, -1, 1, 0]
+opportunities	1.6	0.4899	[1, 1, 2, 2, 2, 1, 2, 2, 1, 2]
+opportunity	1.8	0.6	[2, 2, 2, 2, 3, 1, 2, 1, 1, 2]
+oppressed	-2.1	0.53852	[-2, -2, -2, -1, -2, -2, -3, -2, -2, -3]
+oppressive	-1.7	1.34536	[-3, -2, -1, -2, -2, -2, -3, 2, -2, -2]
+optimal	1.5	0.67082	[1, 2, 1, 3, 1, 1, 1, 2, 2, 1]
+optimality	1.9	0.7	[3, 3, 2, 1, 2, 1, 2, 2, 1, 2]
+optimally	1.3	0.9	[0, 3, 0, 1, 1, 2, 1, 1, 2, 2]
+optimisation	1.6	0.8	[3, 1, 1, 1, 2, 1, 1, 3, 2, 1]
+optimisations	1.8	0.6	[3, 1, 1, 2, 1, 2, 2, 2, 2, 2]
+optimise	1.9	0.83066	[1, 2, 3, 2, 3, 3, 2, 1, 1, 1]
+optimised	1.7	1.26886	[2, 4, 1, 2, 1, 2, 3, 2, 1, -1]
+optimises	1.6	1.0198	[3, 1, 1, 1, 1, 3, 2, 0, 3, 1]
+optimising	1.7	1.00499	[1, 2, 3, 3, 1, 2, 1, 3, 0, 1]
+optimism	2.5	0.67082	[2, 2, 3, 3, 3, 4, 2, 2, 2, 2]
+optimisms	2.0	0.63246	[2, 3, 1, 3, 1, 2, 2, 2, 2, 2]
+optimist	2.4	0.4899	[3, 2, 3, 2, 3, 3, 2, 2, 2, 2]
+optimistic	1.3	1.48661	[2, 2, -3, 2, 2, 2, 1, 2, 1, 2]
+optimistically	2.1	0.53852	[3, 2, 2, 2, 3, 2, 1, 2, 2, 2]
+optimists	1.6	0.66332	[3, 2, 2, 1, 2, 1, 2, 1, 1, 1]
+optimization	1.6	0.8	[2, 3, 1, 1, 1, 2, 0, 2, 2, 2]
+optimizations	0.9	1.04403	[0, 2, 0, 2, 1, 0, 3, 1, 0, 0]
+optimize	2.2	0.87178	[2, 3, 3, 2, 1, 2, 4, 2, 2, 1]
+optimized	2.0	0.44721	[1, 3, 2, 2, 2, 2, 2, 2, 2, 2]
+optimizer	1.5	0.67082	[1, 3, 1, 1, 2, 2, 1, 2, 1, 1]
+optimizers	2.1	0.7	[3, 3, 1, 3, 2, 2, 1, 2, 2, 2]
+optimizes	1.8	0.6	[1, 3, 2, 1, 2, 2, 1, 2, 2, 2]
+optimizing	2.0	0.7746	[1, 1, 2, 2, 1, 3, 3, 3, 2, 2]
+optionless	-1.7	0.64031	[-2, -1, -2, -3, -1, -2, -2, -2, -1, -1]
+original	1.3	0.9	[0, 2, 0, 2, 2, 0, 2, 1, 2, 2]
+outcry	-2.3	0.64031	[-3, -2, -2, -3, -2, -1, -3, -2, -2, -3]
+outgoing	1.2	1.16619	[1, 1, 1, 2, -1, 1, 3, 3, 0, 1]
+outmaneuvered	0.5	1.36015	[-2, 2, 0, 0, 3, 1, 1, 0, 1, -1]
+outrage	-2.3	1.00499	[-2, -2, -4, -3, -1, -3, -3, -1, -1, -3]
+outraged	-2.5	0.92195	[-3, -2, -2, -1, -3, -3, -1, -4, -3, -3]
+outrageous	-2.0	1.34164	[-3, 0, -2, -1, -3, 0, -3, -3, -4, -1]
+outrageously	-1.2	1.32665	[-1, -1, -3, -3, -2, -1, 2, -1, -1, -1]
+outrageousness	-1.2	1.249	[-2, 0, 1, -2, -1, -1, -3, 0, -1, -3]
+outrageousnesses	-1.3	1.67631	[-1, -3, -2, 1, 0, 1, 0, -3, -2, -4]
+outrages	-2.3	1.00499	[-3, -2, -2, -1, -3, -3, -1, -4, -1, -3]
+outraging	-2.0	1.18322	[-4, -1, -2, -3, -1, 0, -1, -3, -3, -2]
+outreach	1.1	0.7	[2, 1, 0, 0, 2, 1, 1, 1, 2, 1]
+outstanding	3.0	0.89443	[3, 1, 3, 3, 4, 4, 2, 3, 4, 3]
+overjoyed	2.7	0.78102	[4, 3, 3, 4, 2, 2, 2, 2, 3, 2]
+overload	-1.5	0.67082	[-2, 0, -1, -2, -2, -1, -1, -2, -2, -2]
+overlooked	-0.1	1.44568	[-1, -2, -1, -1, 2, 0, -1, 2, -1, 2]
+overreact	-1.0	1.73205	[-2, -2, -2, -2, 0, -3, 1, 3, -1, -2]
+overreacted	-1.7	0.64031	[-2, -2, -2, -1, -1, -1, -1, -3, -2, -2]
+overreaction	-0.7	1.34536	[-2, -1, 0, -1, -1, 3, -2, -1, -1, -1]
+overreacts	-2.2	0.87178	[-2, -2, -2, -3, -4, -1, -3, -1, -2, -2]
+oversell	-0.9	0.7	[0, -1, -1, 0, -2, -1, -1, -1, -2, 0]
+overselling	-0.8	1.16619	[0, -1, 0, -1, -2, -1, -1, -2, -2, 2]
+oversells	0.3	1.26886	[-1, -1, 0, 0, 2, 2, 2, -1, 1, -1]
+oversimplification	0.2	1.53623	[-1, 1, -1, -1, 1, -1, -2, 1, 2, 3]
+oversimplifies	0.1	1.37477	[3, 0, 0, -1, 1, -1, 2, -1, -1, -1]
+oversimplify	-0.6	1.35647	[-3, -1, 0, -2, 0, 1, 2, -1, -1, -1]
+overstatement	-1.1	0.7	[-2, 0, -1, -2, -1, 0, -1, -1, -2, -1]
+overstatements	-0.7	1.34536	[-1, -1, -3, -1, 2, 0, -1, -1, -2, 1]
+overweight	-1.5	0.67082	[-3, -2, -1, -1, -1, -2, -1, -2, -1, -1]
+overwhelm	-0.7	1.26886	[-1, 2, -1, -1, -2, -2, 1, 0, -1, -2]
+overwhelmed	0.2	1.53623	[-2, -1, 2, -2, 2, 1, -1, 2, 1, 0]
+overwhelmingly	-0.5	1.28452	[0, -2, -1, 0, -2, -1, -2, 0, 1, 2]
+overwhelms	-0.8	1.249	[-2, -2, -1, -1, -1, -2, 2, 1, -1, -1]
+oxymoron	-0.5	0.80623	[0, 0, -1, -1, -1, -2, 1, 0, 0, -1]
+pain	-2.3	0.64031	[-2, -3, -2, -2, -2, -2, -2, -2, -2, -4]
+pained	-1.8	0.6	[-1, -2, -3, -2, -2, -2, -2, -1, -1, -2]
+painful	-1.9	0.9434	[-2, -1, -1, -3, -4, -1, -1, -2, -2, -2]
+painfuller	-1.7	1.34536	[-2, -2, -2, 2, -1, -3, -2, -2, -3, -2]
+painfully	-2.4	0.4899	[-2, -3, -2, -3, -3, -2, -2, -2, -2, -3]
+painfulness	-2.7	0.64031	[-3, -4, -3, -2, -3, -3, -3, -2, -2, -2]
+paining	-1.7	0.45826	[-1, -2, -2, -2, -2, -2, -1, -2, -1, -2]
+painless	1.2	0.87178	[1, 2, -1, 1, 2, 1, 2, 1, 2, 1]
+painlessly	1.1	0.3	[1, 1, 1, 1, 1, 1, 1, 1, 1, 2]
+painlessness	0.4	1.0198	[1, 1, 1, 1, -1, 1, -2, 0, 1, 1]
+pains	-1.8	0.6	[-2, -2, -1, -1, -1, -2, -2, -2, -3, -2]
+palatable	1.6	0.8	[2, 1, 2, 1, 2, 1, 3, 0, 2, 2]
+palatableness	0.8	0.87178	[2, 1, 1, 0, -1, 2, 0, 1, 1, 1]
+palatably	1.1	0.83066	[2, 1, 2, 1, 1, 1, 2, -1, 1, 1]
+panic	-2.3	0.64031	[-3, -2, -1, -2, -2, -2, -3, -3, -2, -3]
+panicked	-2.0	1.61245	[-2, -4, -3, -3, -3, 1, -2, -2, 1, -3]
+panicking	-1.9	0.53852	[-2, -2, -3, -2, -2, -2, -2, -2, -1, -1]
+panicky	-1.5	0.67082	[-2, -2, -1, -1, -1, -1, -1, -2, -3, -1]
+panicle	0.5	0.67082	[2, 0, 0, 0, 0, 0, 0, 1, 1, 1]
+panicled	0.1	0.83066	[2, 0, 0, 0, 0, -1, 0, -1, 1, 0]
+panicles	-0.2	0.6	[1, 0, 0, 0, 0, -1, 0, -1, -1, 0]
+panics	-1.9	1.3	[-2, -3, -2, -3, -1, -2, 1, -4, -1, -2]
+paniculate	0.1	0.3	[0, 0, 0, 1, 0, 0, 0, 0, 0, 0]
+panicums	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+paradise	3.2	0.9798	[4, 1, 4, 2, 4, 4, 3, 3, 3, 4]
+paradox	-0.4	0.66332	[-1, -1, 0, 0, -1, 0, -1, 0, 1, -1]
+paranoia	-1.0	1.48324	[1, -2, -2, -3, -1, 0, -2, -1, -2, 2]
+paranoiac	-1.3	1.61555	[-2, -3, -2, -2, 1, -3, 2, -2, 0, -2]
+paranoiacs	-0.7	1.18743	[-1, 0, -1, -1, -3, 1, -2, 0, 1, -1]
+paranoias	-1.5	1.0247	[-2, -3, -2, 0, -1, -3, 0, -1, -1, -2]
+paranoid	-1.0	1.41421	[0, -3, -3, -2, -1, -1, 0, 1, -2, 1]
+paranoids	-1.6	0.91652	[-2, -1, -1, -2, -2, -1, -1, -1, -4, -1]
+pardon	1.3	0.45826	[1, 2, 1, 2, 1, 2, 1, 1, 1, 1]
+pardoned	0.9	0.9434	[1, 1, 1, 1, 1, 1, 1, 0, 3, -1]
+pardoning	1.7	0.78102	[3, 2, 2, 2, 1, 1, 2, 2, 0, 2]
+pardons	1.2	0.6	[2, 1, 1, 1, 1, 2, 1, 2, 0, 1]
+parley	-0.4	0.66332	[0, -2, 0, 0, -1, -1, 0, 0, 0, 0]
+partied	1.4	1.11355	[2, 3, 1, 1, 1, 2, 3, -1, 1, 1]
+partier	1.4	0.8	[2, 2, 1, 1, 0, 2, 3, 1, 1, 1]
+partiers	0.7	1.00499	[0, 0, 3, 0, 0, 0, 2, 1, 0, 1]
+parties	1.7	0.78102	[2, 3, 1, 1, 1, 2, 3, 1, 2, 1]
+party	1.7	0.78102	[3, 2, 2, 1, 3, 2, 1, 1, 1, 1]
+partyer	1.2	1.07703	[1, 3, 1, 0, 1, 0, 2, 1, 3, 0]
+partyers	1.1	0.83066	[1, 2, 0, 3, 1, 1, 1, 0, 1, 1]
+partying	1.6	1.11355	[0, 3, 1, 0, 3, 2, 3, 1, 2, 1]
+passion	2.0	0.44721	[2, 2, 1, 3, 2, 2, 2, 2, 2, 2]
+passional	1.6	0.8	[2, 1, 3, 0, 2, 1, 1, 2, 2, 2]
+passionate	2.4	1.35647	[0, 4, 3, 3, 4, 2, 0, 2, 3, 3]
+passionately	2.4	0.91652	[3, 0, 3, 3, 2, 3, 2, 3, 2, 3]
+passionateness	2.3	0.64031	[1, 3, 2, 3, 2, 3, 2, 3, 2, 2]
+passionflower	0.3	0.45826	[0, 0, 0, 0, 1, 0, 1, 1, 0, 0]
+passionflowers	0.4	0.66332	[0, 0, 0, 0, 2, 1, 1, 0, 0, 0]
+passionless	-1.9	0.7	[-3, -2, -2, -2, -1, -1, -1, -3, -2, -2]
+passions	2.2	0.6	[3, 3, 3, 2, 2, 1, 2, 2, 2, 2]
+passive	0.8	1.46969	[4, 1, 1, 0, -2, 0, 1, 1, 2, 0]
+passively	-0.7	0.64031	[0, -1, 0, 0, -1, -2, 0, -1, -1, -1]
+pathetic	-2.7	1.48661	[-3, -4, -3, -4, -2, 1, -2, -2, -4, -4]
+pathetical	-1.2	1.249	[-2, -1, -2, -1, -2, 1, -3, 1, -1, -2]
+pathetically	-1.8	1.72047	[-3, -4, -2, 0, -3, -2, -3, -3, 1, 1]
+pay	-0.4	0.91652	[0, 0, -3, 0, 0, 0, 0, 0, -1, 0]
+peace	2.5	1.0247	[3, 2, 1, 4, 2, 3, 4, 1, 3, 2]
+peaceable	1.7	0.45826	[2, 2, 1, 2, 1, 2, 2, 1, 2, 2]
+peaceableness	1.8	1.16619	[2, 2, 4, 2, 2, 2, 2, 1, 2, -1]
+peaceably	2.0	0.63246	[2, 3, 2, 2, 1, 2, 3, 1, 2, 2]
+peaceful	2.2	0.74833	[4, 2, 1, 2, 2, 2, 3, 2, 2, 2]
+peacefuller	1.9	0.7	[2, 2, 2, 1, 3, 3, 2, 2, 1, 1]
+peacefullest	3.1	0.7	[3, 3, 2, 3, 4, 2, 4, 3, 4, 3]
+peacefully	2.4	0.66332	[3, 2, 2, 2, 4, 2, 2, 3, 2, 2]
+peacefulness	2.1	0.83066	[3, 2, 1, 2, 3, 1, 3, 3, 1, 2]
+peacekeeper	1.6	1.11355	[1, 1, 0, 2, 1, 1, 4, 3, 2, 1]
+peacekeepers	1.6	1.11355	[4, 1, 1, 2, 1, 1, 2, 3, 0, 1]
+peacekeeping	2.0	0.63246	[2, 1, 1, 2, 3, 3, 2, 2, 2, 2]
+peacekeepings	1.6	0.8	[0, 1, 1, 2, 2, 3, 2, 2, 2, 1]
+peacemaker	2.0	0.89443	[2, 1, 2, 4, 2, 2, 1, 3, 1, 2]
+peacemakers	2.4	1.0198	[0, 3, 4, 2, 3, 2, 3, 3, 2, 2]
+peacemaking	1.7	0.78102	[1, 1, 1, 3, 3, 1, 2, 2, 2, 1]
+peacenik	0.8	0.87178	[1, 1, 0, 1, 2, 0, 1, 1, -1, 2]
+peaceniks	0.7	1.00499	[2, 0, 0, 1, 0, 2, 1, -1, 2, 0]
+peaces	2.1	0.83066	[2, 2, 2, 2, 3, 0, 3, 3, 2, 2]
+peacetime	2.2	1.16619	[3, 1, 4, 2, 4, 3, 1, 1, 2, 1]
+peacetimes	2.1	0.83066	[3, 2, 2, 4, 1, 2, 2, 2, 1, 2]
+peculiar	0.6	1.2	[-1, 0, -1, 1, 2, -1, 2, 1, 2, 1]
+peculiarities	0.1	1.37477	[-1, -1, 0, -1, -1, 1, 3, 2, -1, 0]
+peculiarity	0.6	1.2	[-1, 1, -1, 0, 2, -1, 1, 2, 2, 1]
+peculiarly	-0.4	1.2	[-1, 2, -2, -1, 0, 0, -2, 1, -1, 0]
+penalty	-2.0	0.63246	[-2, -3, -2, -2, -1, -2, -3, -2, -2, -1]
+pensive	0.3	1.1	[1, 0, 0, 1, 0, -1, 3, 0, -1, 0]
+perfect	2.7	0.78102	[2, 4, 2, 3, 4, 2, 3, 2, 3, 2]
+perfecta	1.4	1.42829	[1, 0, 0, 3, 1, 0, 0, 4, 3, 2]
+perfectas	0.6	1.11355	[0, 0, -1, 1, 0, 2, 3, 0, 1, 0]
+perfected	2.7	0.78102	[1, 3, 3, 4, 2, 3, 3, 2, 3, 3]
+perfecter	1.8	0.9798	[2, 1, 3, 1, 2, 1, 2, 4, 1, 1]
+perfecters	1.4	1.11355	[2, 1, 3, 0, 0, 3, 2, 0, 1, 2]
+perfectest	3.1	1.04403	[2, 4, 4, 4, 3, 2, 1, 3, 4, 4]
+perfectibilities	2.1	1.04403	[3, 2, 2, 3, 4, 1, 2, 2, 0, 2]
+perfectibility	1.8	1.249	[4, 3, 3, 0, 1, 0, 1, 2, 2, 2]
+perfectible	1.5	0.67082	[1, 2, 1, 1, 2, 1, 1, 3, 2, 1]
+perfecting	2.3	0.9	[1, 2, 3, 3, 1, 2, 2, 4, 2, 3]
+perfection	2.7	1.1	[3, 3, 3, 1, 2, 4, 4, 1, 2, 4]
+perfectionism	1.3	1.26886	[3, -1, 2, 1, 2, 2, 2, -1, 1, 2]
+perfectionist	1.5	1.20416	[3, -1, 3, 1, 2, 2, 2, 0, 1, 2]
+perfectionistic	0.7	1.67631	[-1, 0, 2, 0, 1, 0, 3, -1, 4, -1]
+perfectionists	0.1	1.22066	[1, -1, 1, -1, 0, 0, -1, 0, 3, -1]
+perfections	2.5	1.43178	[2, 4, 4, 3, 3, 4, -1, 2, 2, 2]
+perfective	1.2	0.87178	[1, 0, 1, 1, 3, 2, 2, 0, 1, 1]
+perfectively	2.1	1.13578	[3, 3, 1, 4, 0, 2, 1, 2, 2, 3]
+perfectiveness	0.9	1.51327	[-2, 3, -1, 0, 2, 0, 2, 2, 2, 1]
+perfectives	0.9	0.83066	[0, 2, 1, 1, 1, 0, 2, 0, 2, 0]
+perfectivity	2.2	0.9798	[3, 2, 0, 3, 1, 2, 3, 3, 2, 3]
+perfectly	3.2	0.4	[3, 4, 4, 3, 3, 3, 3, 3, 3, 3]
+perfectness	3.0	0.63246	[4, 3, 3, 3, 3, 2, 4, 2, 3, 3]
+perfecto	1.3	1.34536	[1, 0, 0, 2, 0, 0, 1, 4, 3, 2]
+perfects	1.6	1.11355	[1, 1, 1, 2, 1, 0, 1, 4, 3, 2]
+peril	-1.7	1.67631	[-3, -2, -2, 3, -3, -2, -3, -2, -1, -2]
+perjury	-1.9	0.9434	[-3, -2, -3, -2, -2, 0, -1, -2, -3, -1]
+perpetrator	-2.2	0.74833	[-2, -3, -2, -2, -2, -2, -4, -2, -1, -2]
+perpetrators	-1.0	1.67332	[-1, -2, -2, -2, -2, 2, 0, -4, 1, 0]
+perplexed	-1.3	0.64031	[-1, -1, -2, -1, -1, -1, 0, -2, -2, -2]
+persecute	-2.1	1.37477	[-2, -3, -2, 1, -1, -4, -2, -2, -2, -4]
+persecuted	-1.3	1.61555	[-2, -1, -2, -1, -2, 2, -4, 1, -2, -2]
+persecutes	-1.2	1.4	[-2, -1, -2, 0, -2, 1, -3, 1, -1, -3]
+persecuting	-1.5	1.62788	[-3, -2, -2, 0, -4, -3, -2, -1, 1, 1]
+perturbed	-1.4	0.8	[-2, -1, -1, 0, -2, -2, -2, 0, -2, -2]
+perverse	-1.8	1.8868	[-2, -4, -3, 1, -2, -4, 1, 0, -1, -4]
+perversely	-2.2	0.87178	[-1, -2, -2, -2, -1, -3, -2, -3, -4, -2]
+perverseness	-2.1	1.22066	[-3, -3, 1, -2, -3, -2, -3, -2, -1, -3]
+perversenesses	-0.5	1.74642	[-2, 3, -1, -2, 1, 0, 1, 0, -2, -3]
+perversion	-1.3	1.34536	[-3, -2, -2, 1, 1, -3, -1, -2, -1, -1]
+perversions	-1.2	1.83303	[-2, 0, -4, -2, -3, -3, 0, 1, -1, 2]
+perversities	-1.1	1.22066	[-2, -1, -2, 0, -2, -2, -2, 1, 1, -2]
+perversity	-2.6	0.8	[-2, -3, -2, -2, -4, -3, -3, -1, -3, -3]
+perversive	-2.1	0.7	[-3, -1, -3, -2, -2, -2, -2, -1, -3, -2]
+pervert	-2.3	0.9	[-2, -2, -1, -3, -4, -2, -3, -1, -3, -2]
+perverted	-2.5	1.56525	[-2, -4, -2, -4, -3, -4, 1, -2, -1, -4]
+pervertedly	-1.2	1.77764	[-3, -2, -1, -2, 2, -3, 1, -3, 1, -2]
+pervertedness	-1.2	1.46969	[1, -2, -3, -2, 0, -2, -3, 1, 0, -2]
+perverter	-1.7	1.48661	[-3, -4, -2, -2, -1, -1, 2, -2, -2, -2]
+perverters	-0.6	1.68523	[-2, -2, -1, 0, -1, 2, -3, 1, 2, -2]
+perverting	-1.0	2.09762	[4, -2, -2, -4, -2, 1, 0, -1, -2, -2]
+perverts	-2.8	0.6	[-3, -3, -2, -3, -3, -2, -2, -4, -3, -3]
+pesky	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
+pessimism	-1.5	1.36015	[-2, -3, 1, -2, -2, -1, 1, -3, -2, -2]
+pessimisms	-2.0	1.0	[-3, -1, -2, -2, -3, -1, 0, -2, -3, -3]
+pessimist	-1.5	1.36015	[-1, -3, 1, -2, -2, -2, 1, -3, -2, -2]
+pessimistic	-1.5	1.43178	[-3, -1, -1, 1, -3, -3, -2, -2, -2, 1]
+pessimistically	-2.0	1.0	[-1, -1, -3, -4, -2, -1, -1, -3, -2, -2]
+pessimists	-1.0	1.26491	[-1, 1, -1, 0, -2, -2, -2, -3, -1, 1]
+petrifaction	-1.9	1.3	[-3, -2, -1, -4, -3, 0, -1, 0, -2, -3]
+petrifactions	-0.3	1.00499	[0, -1, 0, 0, 0, 0, 0, 0, -3, 1]
+petrification	-0.1	1.44568	[-1, 2, -1, -1, 0, 2, 2, -2, -1, -1]
+petrifications	-0.4	0.8	[0, 0, -2, 0, 0, 0, 0, 0, -2, 0]
+petrified	-2.5	0.92195	[-4, -3, -2, -1, -2, -3, -2, -2, -2, -4]
+petrifies	-2.3	1.00499	[-4, -3, -2, -1, -2, -2, -1, -2, -2, -4]
+petrify	-1.7	0.9	[-2, -3, -1, -2, -1, -1, -2, -3, 0, -2]
+petrifying	-2.6	0.8	[-2, -3, -3, -2, -4, -2, -3, -1, -3, -3]
+pettier	-0.3	1.41774	[-1, -1, -1, -1, 2, 0, 2, -2, 1, -2]
+pettiest	-1.3	1.95192	[1, -3, -3, -3, -2, -1, 2, -1, 1, -4]
+petty	-0.8	1.32665	[1, -3, -2, -1, -1, -1, -1, -1, 2, -1]
+phobia	-1.6	1.0198	[-2, -2, 1, -2, -3, -1, -1, -2, -2, -2]
+phobias	-2.0	1.0	[-3, -2, -2, -3, -3, 0, -1, -2, -1, -3]
+phobic	-1.2	1.16619	[-2, -2, 1, -1, -2, -1, 1, -2, -2, -2]
+phobics	-1.3	0.64031	[-1, -1, -1, -2, -2, -1, 0, -2, -2, -1]
+picturesque	1.6	1.11355	[4, 1, 1, 2, 1, 2, 1, 0, 3, 1]
+pileup	-1.1	1.13578	[-2, 1, 0, -1, 0, -1, -3, -2, -2, -1]
+pique	-1.1	1.13578	[-2, -2, -2, 0, 0, -1, 1, -1, -1, -3]
+piqued	0.1	1.04403	[0, -2, 0, 1, 1, 1, -1, 1, -1, 1]
+piss	-1.7	0.9	[-2, -1, -1, -2, -1, -3, -3, 0, -2, -2]
+pissant	-1.5	1.5	[-1, -3, -3, 1, -3, -1, -1, -2, 1, -3]
+pissants	-2.5	0.80623	[-4, -3, -3, -2, -3, -1, -2, -3, -2, -2]
+pissed	-3.2	0.6	[-3, -3, -4, -3, -2, -4, -4, -3, -3, -3]
+pisser	-2.0	1.09545	[-2, -4, -1, -3, -2, -3, -1, -2, -2, 0]
+pissers	-1.4	2.00998	[-1, -1, -4, -2, -3, 4, -2, -1, -2, -2]
+pisses	-1.4	0.8	[-2, -2, -1, -3, -1, -1, -1, -2, -1, 0]
+pissing	-1.7	1.26886	[0, 0, -2, -2, -3, 0, -3, -1, -3, -3]
+pissoir	-0.8	1.4	[-2, 0, 0, -2, -1, -3, 0, -2, 0, 2]
+piteous	-1.2	1.46969	[-2, -1, -2, -2, -2, -1, 3, -1, -2, -2]
+pitiable	-1.1	1.22066	[-1, 0, -1, -1, 1, -2, -4, -1, -1, -1]
+pitiableness	-1.1	1.64012	[-2, -1, -1, -2, -4, 2, 1, 0, -2, -2]
+pitiably	-1.1	0.9434	[-1, 0, 0, -2, 0, -2, -3, -1, -1, -1]
+pitied	-1.3	1.1	[-2, -1, -3, -1, 1, 0, -2, -2, -1, -2]
+pitier	-1.2	1.32665	[-3, -1, -2, -3, -1, -1, 1, 1, -2, -1]
+pitiers	-1.3	0.9	[0, -1, -2, -2, -1, -1, -1, -3, -2, 0]
+pities	-1.2	1.249	[-2, -1, -2, -3, -1, -1, 1, 1, -2, -2]
+pitiful	-2.2	0.9798	[-3, -2, -1, -3, -2, -2, -3, -3, -3, 0]
+pitifuller	-1.8	1.07703	[-1, -1, -2, -3, -4, 0, -2, -2, -1, -2]
+pitifullest	-1.1	2.11896	[-2, 1, -1, -4, -4, -1, -3, -1, 2, 2]
+pitifully	-1.2	1.249	[-2, -1, -3, -2, -1, -1, -2, -1, 2, -1]
+pitifulness	-1.2	1.77764	[-3, -2, -1, -3, -2, -1, 3, 1, -2, -2]
+pitiless	-1.8	0.87178	[-2, 0, -2, -2, -2, -3, -1, -3, -1, -2]
+pitilessly	-2.1	0.7	[-2, -2, -1, -3, -3, -1, -3, -2, -2, -2]
+pitilessness	-0.5	1.62788	[1, 3, 1, -3, -2, -1, -1, -1, -1, -1]
+pity	-1.2	0.4	[-2, -2, -1, -1, -1, -1, -1, -1, -1, -1]
+pitying	-1.4	0.91652	[-1, -3, -1, -3, -2, -1, 0, -1, -1, -1]
+pityingly	-1.0	1.26491	[-2, -2, -1, -2, -2, 0, 0, -1, 2, -2]
+pityriasis	-0.8	0.87178	[-2, 0, 0, 0, -1, 0, -2, -1, -2, 0]
+play	1.4	1.0198	[2, 0, 1, 1, 1, 2, 1, 4, 1, 1]
+played	1.4	1.42829	[2, 1, 1, 1, 4, 0, 1, 0, 4, 0]
+playful	1.9	0.83066	[4, 2, 2, 2, 1, 1, 1, 2, 2, 2]
+playfully	1.6	0.4899	[2, 1, 1, 2, 1, 2, 2, 2, 1, 2]
+playfulness	1.2	0.87178	[2, 1, 2, -1, 1, 2, 1, 2, 1, 1]
+playing	0.8	0.87178	[0, 2, 2, 1, 0, 0, 2, 0, 0, 1]
+plays	1.0	1.09545	[0, 2, 0, 2, 0, 1, 0, 2, 3, 0]
+pleasant	2.3	0.64031	[2, 3, 3, 3, 2, 1, 2, 2, 3, 2]
+pleasanter	1.5	0.67082	[2, 2, 2, 1, 0, 1, 1, 2, 2, 2]
+pleasantest	2.6	0.8	[3, 3, 3, 1, 2, 4, 3, 2, 2, 3]
+pleasantly	2.1	0.53852	[1, 2, 3, 2, 2, 2, 2, 2, 3, 2]
+pleasantness	2.3	0.9	[3, 2, 3, 3, 3, 1, 1, 3, 1, 3]
+pleasantnesses	2.3	0.78102	[3, 1, 2, 3, 1, 2, 3, 3, 2, 3]
+pleasantries	1.3	0.45826	[1, 1, 1, 1, 1, 2, 1, 2, 2, 1]
+pleasantry	2.0	0.7746	[2, 2, 1, 1, 4, 2, 2, 2, 2, 2]
+please	1.3	0.78102	[2, 1, 2, 2, 2, 0, 2, 1, 0, 1]
+pleased	1.9	0.53852	[2, 2, 2, 2, 1, 1, 2, 3, 2, 2]
+pleaser	1.7	0.45826	[2, 2, 2, 2, 1, 1, 1, 2, 2, 2]
+pleasers	1.0	1.0	[1, 1, 2, 0, 1, 3, 1, 1, -1, 1]
+pleases	1.7	0.45826	[2, 1, 2, 2, 1, 1, 2, 2, 2, 2]
+pleasing	2.4	0.91652	[2, 3, 2, 2, 2, 2, 4, 4, 1, 2]
+pleasurability	1.9	0.83066	[1, 2, 2, 2, 2, 0, 2, 3, 3, 2]
+pleasurable	2.4	0.4899	[2, 3, 3, 2, 3, 3, 2, 2, 2, 2]
+pleasurableness	2.4	0.91652	[2, 3, 2, 1, 2, 3, 4, 3, 1, 3]
+pleasurably	2.6	0.4899	[2, 2, 2, 3, 3, 3, 3, 2, 3, 3]
+pleasure	2.7	0.9	[4, 4, 3, 2, 2, 3, 2, 1, 3, 3]
+pleasured	2.3	0.64031	[3, 2, 3, 2, 3, 3, 1, 2, 2, 2]
+pleasureless	-1.6	0.8	[-1, -1, -1, -1, -2, -3, -3, -2, -1, -1]
+pleasures	1.9	1.37477	[3, -2, 3, 2, 3, 2, 2, 2, 2, 2]
+pleasuring	2.8	0.4	[3, 2, 3, 3, 3, 3, 3, 2, 3, 3]
+poised	1.0	0.44721	[1, 1, 1, 1, 1, 1, 0, 1, 1, 2]
+poison	-2.5	0.92195	[-4, -3, -2, -4, -2, -2, -2, -3, -1, -2]
+poisoned	-2.2	0.9798	[-4, -1, -4, -1, -2, -2, -2, -2, -2, -2]
+poisoner	-2.7	0.78102	[-2, -3, -3, -4, -4, -2, -2, -2, -2, -3]
+poisoners	-3.1	0.83066	[-3, -4, -3, -4, -3, -4, -3, -3, -1, -3]
+poisoning	-2.8	1.249	[-4, -4, -2, 0, -2, -3, -4, -3, -2, -4]
+poisonings	-2.4	1.11355	[-2, 0, -2, -1, -4, -3, -3, -3, -3, -3]
+poisonous	-2.7	0.78102	[-3, -3, -4, -2, -1, -3, -3, -3, -3, -2]
+poisonously	-2.9	0.53852	[-3, -2, -3, -3, -2, -3, -3, -4, -3, -3]
+poisons	-2.7	0.9	[-3, -4, -3, -1, -2, -3, -3, -2, -2, -4]
+poisonwood	-1.0	0.89443	[0, -2, 0, 0, 0, -1, -2, -2, -2, -1]
+pollute	-2.3	0.64031	[-3, -2, -2, -2, -2, -3, -3, -1, -3, -2]
+polluted	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -2, -3, -2]
+polluter	-1.8	0.6	[-2, -1, -2, -1, -2, -2, -3, -1, -2, -2]
+polluters	-2.0	0.44721	[-2, -2, -2, -2, -2, -3, -2, -1, -2, -2]
+pollutes	-2.2	0.87178	[-2, -1, -2, -1, -3, -1, -3, -3, -3, -3]
+poor	-2.1	1.13578	[-2, -2, -1, -4, -2, 0, -2, -4, -2, -2]
+poorer	-1.5	1.56525	[-2, -3, -2, -2, -2, -2, 3, -2, -1, -2]
+poorest	-2.5	0.80623	[-2, -3, -3, -1, -2, -3, -3, -4, -2, -2]
+popular	1.8	0.74833	[2, 3, 1, 2, 2, 1, 3, 1, 2, 1]
+popularise	1.6	0.66332	[1, 1, 2, 2, 3, 2, 1, 2, 1, 1]
+popularised	1.1	0.9434	[1, 1, 0, 0, 3, 2, 1, 2, 1, 0]
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+popularising	1.2	0.6	[1, 0, 2, 2, 1, 1, 1, 2, 1, 1]
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+popularity	2.1	1.04403	[2, 1, 1, 1, 3, 2, 3, 4, 3, 1]
+popularization	1.3	0.78102	[1, 2, 1, 2, 1, 0, 1, 1, 3, 1]
+popularizations	0.9	0.7	[1, 1, 1, 0, 2, 0, 1, 1, 2, 0]
+popularize	1.3	0.64031	[2, 2, 0, 2, 1, 1, 1, 1, 2, 1]
+popularized	1.9	0.83066	[3, 2, 3, 2, 1, 0, 2, 2, 2, 2]
+popularizer	1.8	0.74833	[2, 2, 3, 2, 1, 0, 2, 2, 2, 2]
+popularizers	1.0	0.89443	[0, 0, 1, 2, 1, 1, 1, 1, 3, 0]
+popularizes	1.4	0.8	[2, 1, 3, 2, 1, 0, 1, 2, 1, 1]
+popularizing	1.5	0.67082	[2, 2, 1, 1, 1, 2, 2, 0, 2, 2]
+popularly	1.8	0.74833	[1, 3, 2, 1, 3, 1, 2, 1, 2, 2]
+positive	2.6	0.91652	[2, 1, 2, 2, 3, 3, 4, 3, 4, 2]
+positively	2.4	0.66332	[2, 2, 3, 3, 4, 2, 2, 2, 2, 2]
+positiveness	2.3	1.18743	[2, 1, 4, 3, 4, 2, 0, 3, 2, 2]
+positivenesses	2.2	0.74833	[3, 3, 2, 2, 2, 2, 1, 3, 1, 3]
+positiver	2.3	0.78102	[1, 4, 2, 2, 2, 3, 2, 2, 2, 3]
+positives	2.4	0.4899	[3, 3, 2, 2, 2, 2, 3, 2, 3, 2]
+positivest	2.9	1.04403	[4, 3, 2, 1, 3, 4, 4, 4, 2, 2]
+positivism	1.6	1.35647	[3, 0, 2, 1, 2, 0, 3, 4, 1, 0]
+positivisms	1.8	0.9798	[4, 1, 2, 2, 2, 0, 2, 2, 1, 2]
+positivist	2.0	1.0	[3, 1, 2, 2, 2, 0, 2, 4, 2, 2]
+positivistic	1.9	0.83066	[2, 3, 1, 3, 1, 1, 3, 2, 1, 2]
+positivists	1.7	1.1	[1, 2, 1, 4, 2, 1, 3, 0, 1, 2]
+positivities	2.6	0.91652	[2, 2, 4, 3, 2, 3, 4, 3, 1, 2]
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+possessive	-0.9	1.22066	[-1, -1, -2, -2, 0, -1, 0, -2, 2, -2]
+postpone	-0.9	0.83066	[1, -1, -2, -1, -1, -2, -1, -1, 0, -1]
+postponed	-0.8	0.4	[-1, -1, 0, 0, -1, -1, -1, -1, -1, -1]
+postpones	-1.1	0.83066	[-1, -1, -1, 0, -1, 0, -2, -1, -3, -1]
+postponing	-0.5	0.5	[0, -1, 0, -1, 0, 0, 0, -1, -1, -1]
+poverty	-2.3	1.00499	[-2, -4, -2, -4, -3, -1, -2, -2, -1, -2]
+powerful	1.8	0.9798	[4, 0, 2, 1, 2, 2, 2, 2, 1, 2]
+powerless	-2.2	0.6	[-2, -3, -2, -2, -3, -2, -3, -2, -1, -2]
+praise	2.6	0.8	[2, 4, 3, 3, 2, 1, 3, 3, 2, 3]
+praised	2.2	0.6	[3, 2, 2, 2, 2, 3, 1, 3, 2, 2]
+praiser	2.0	0.89443	[3, 1, 3, 1, 1, 2, 1, 3, 2, 3]
+praisers	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
+praises	2.4	0.4899	[3, 2, 2, 3, 2, 3, 2, 3, 2, 2]
+praiseworthily	1.9	0.7	[2, 1, 1, 3, 2, 2, 2, 3, 1, 2]
+praiseworthiness	2.4	0.8	[1, 3, 2, 4, 2, 2, 3, 2, 3, 2]
+praiseworthy	2.6	0.4899	[3, 3, 3, 3, 2, 2, 3, 2, 3, 2]
+praising	2.5	0.67082	[2, 3, 3, 2, 2, 3, 3, 3, 1, 3]
+pray	1.3	1.18743	[0, 3, 2, 1, 1, 1, -1, 3, 1, 2]
+praying	1.5	0.92195	[2, 2, 0, 3, 1, 3, 1, 1, 1, 1]
+prays	1.4	1.0198	[2, 0, 2, 0, 1, 1, 3, 1, 3, 1]
+prblm	-1.6	0.8	[-1, -1, -1, -1, -1, -3, -3, -2, -2, -1]
+prblms	-2.3	1.00499	[-2, -2, -2, -2, -4, -4, -3, -1, -2, -1]
+precious	2.7	0.64031	[3, 3, 3, 3, 3, 1, 3, 3, 2, 3]
+preciously	2.2	0.74833	[3, 3, 3, 2, 2, 1, 1, 3, 2, 2]
+preciousness	1.9	0.83066	[2, 4, 2, 2, 2, 1, 1, 1, 2, 2]
+prejudice	-2.3	0.78102	[-2, -1, -2, -2, -3, -2, -2, -3, -4, -2]
+prejudiced	-1.9	0.53852	[-2, -3, -1, -2, -1, -2, -2, -2, -2, -2]
+prejudices	-1.8	0.74833	[-2, -3, -1, -2, -1, -3, -2, -1, -1, -2]
+prejudicial	-2.6	0.8	[-3, -3, -2, -2, -3, -4, -2, -1, -3, -3]
+prejudicially	-1.5	1.74642	[-3, -1, -1, -3, -3, -1, -3, 1, 2, -3]
+prejudicialness	-2.4	1.42829	[-2, -3, 1, -3, -2, -4, -4, -3, -1, -3]
+prejudicing	-1.8	1.07703	[-2, -2, -2, -3, -2, -1, 1, -3, -2, -2]
+prepared	0.9	0.3	[1, 1, 1, 1, 1, 0, 1, 1, 1, 1]
+pressure	-1.2	0.6	[-1, -1, -1, -1, -2, -2, -1, -2, 0, -1]
+pressured	-0.9	1.04403	[-2, -1, -2, -1, 2, -1, -1, -1, -1, -1]
+pressureless	1.0	1.26491	[2, 0, 1, -1, -1, 2, 1, 2, 1, 3]
+pressures	-1.3	0.64031	[-2, -1, -1, -1, -3, -1, -1, -1, -1, -1]
+pressuring	-1.4	0.91652	[-3, -1, -1, -1, -1, -1, -1, -3, -2, 0]
+pressurise	-0.6	1.0198	[0, -2, 0, 1, 0, -2, 0, -2, 0, -1]
+pressurised	-0.4	0.66332	[0, 0, 0, -1, 0, -1, 0, -2, 0, 0]
+pressurises	-0.8	0.6	[-1, -1, -1, 0, -1, -1, 0, -1, 0, -2]
+pressurising	-0.6	1.28062	[-1, 0, 0, 2, -1, -1, -3, 0, -2, 0]
+pressurizations	-0.3	1.00499	[0, 0, 1, -2, 0, 0, -1, -2, 0, 1]
+pressurize	-0.7	1.34536	[0, -2, -2, 0, 0, -1, -3, 2, -1, 0]
+pressurized	0.1	0.83066	[0, 0, 0, 2, 0, 0, -1, -1, 0, 1]
+pressurizer	0.1	0.83066	[0, 0, 0, 1, 0, 0, -1, -1, 0, 2]
+pressurizers	-0.7	0.9	[-1, 0, -2, -1, -2, -1, 0, 0, 1, -1]
+pressurizes	-0.2	0.87178	[0, 0, -1, 1, 0, 0, -1, -2, 0, 1]
+pressurizing	-0.2	0.9798	[1, 0, -1, -1, -1, 0, -1, 2, 0, -1]
+pretend	-0.4	0.91652	[0, 1, -1, -1, -2, 0, -1, -1, 1, 0]
+pretending	0.4	1.49666	[2, 0, -1, -1, 0, 3, -2, 1, 0, 2]
+pretends	-0.4	0.66332	[0, -1, 0, -1, 1, 0, 0, -1, -1, -1]
+prettied	1.6	0.66332	[2, 1, 1, 1, 1, 2, 3, 2, 1, 2]
+prettier	2.1	0.53852	[2, 2, 2, 2, 2, 2, 3, 1, 2, 3]
+pretties	1.7	0.78102	[2, 1, 1, 2, 1, 2, 3, 1, 1, 3]
+prettiest	2.7	0.78102	[4, 3, 4, 2, 2, 2, 3, 2, 2, 3]
+pretty	2.2	0.6	[3, 2, 2, 2, 3, 1, 2, 2, 2, 3]
+prevent	0.1	1.22066	[-2, 1, 0, 0, -1, 2, -1, 2, 0, 0]
+prevented	0.1	0.7	[0, -1, 0, 2, 0, 0, 0, 0, 0, 0]
+preventing	-0.1	1.51327	[-2, 0, -2, 3, 0, 0, -1, -1, 2, 0]
+prevents	0.3	1.34536	[0, -2, 0, 0, 0, 2, 0, -1, 3, 1]
+prick	-1.4	1.42829	[-2, -2, -2, -1, 1, -1, -4, -2, 1, -2]
+pricked	-0.6	1.0198	[-1, -1, -2, 1, 0, -1, -2, -1, 1, 0]
+pricker	-0.3	0.9	[-1, -1, 0, 2, 0, -1, -1, -1, 0, 0]
+prickers	-0.2	0.87178	[1, -1, -1, 0, 1, -1, 0, 1, -1, -1]
+pricket	-0.5	0.67082	[0, -1, -1, -2, 0, 0, 0, 0, -1, 0]
+prickets	0.3	0.64031	[0, 2, 0, 0, 0, 1, 0, 0, 0, 0]
+pricking	-0.9	1.22066	[-2, -1, -2, 2, -2, -2, -1, 0, -1, 0]
+prickle	-1.0	0.44721	[-1, -1, -1, -1, -1, -1, -2, 0, -1, -1]
+prickled	-0.2	1.53623	[-1, -1, 3, -1, -2, 2, 0, 0, 0, -2]
+prickles	-0.8	0.74833	[0, -1, -1, -1, -2, -1, 0, 0, 0, -2]
+pricklier	-1.6	0.8	[-1, -2, -2, -2, -2, -1, -2, -1, 0, -3]
+prickliest	-1.4	1.35647	[-4, -2, -1, 0, -3, -1, -1, 1, -2, -1]
+prickliness	-0.6	0.91652	[-2, -1, -1, -1, -1, 1, -1, 1, 0, -1]
+prickling	-0.8	0.6	[-2, -1, 0, -1, 0, 0, -1, -1, -1, -1]
+prickly	-0.9	1.04403	[-2, -1, -1, -2, -1, 1, -2, -1, 1, -1]
+pricks	-0.9	1.04403	[-2, 0, -1, -3, -1, 1, 0, -1, -1, -1]
+pricky	-0.6	1.2	[-2, 1, -1, -2, -1, 2, 0, -1, -1, -1]
+pride	1.4	1.11355	[0, 2, 2, 2, 3, 1, -1, 2, 2, 1]
+prison	-2.3	0.64031	[-3, -3, -2, -2, -1, -2, -3, -3, -2, -2]
+prisoner	-2.5	1.0247	[-3, -1, -4, -4, -3, -2, -3, -2, -1, -2]
+prisoners	-2.3	0.78102	[-3, -2, -3, -3, -1, -3, -2, -1, -2, -3]
+privilege	1.5	0.80623	[2, 1, 0, 1, 3, 1, 2, 2, 2, 1]
+privileged	1.9	0.9434	[2, 3, 3, 2, 3, 1, 1, 2, 0, 2]
+privileges	1.6	1.2	[2, 1, 3, 1, 2, 2, 0, 0, 4, 1]
+privileging	0.7	1.1	[1, 1, 2, 2, -1, 2, 1, 0, 0, -1]
+prize	2.3	1.1	[2, 2, 0, 4, 4, 3, 2, 2, 2, 2]
+prized	2.4	0.8	[3, 3, 3, 2, 3, 2, 1, 3, 1, 3]
+prizefight	-0.1	1.13578	[-2, 2, 0, 0, 0, -2, 0, 1, 0, 0]
+prizefighter	1.0	1.0	[0, 2, 0, 0, 0, 2, 0, 2, 2, 2]
+prizefighters	-0.1	1.04403	[0, 0, -3, 0, 0, 0, 0, 1, 1, 0]
+prizefighting	0.4	0.91652	[0, 0, 0, 1, 0, 3, 0, 0, 0, 0]
+prizefights	0.3	0.78102	[1, 2, 0, 0, -1, 0, 0, 1, 0, 0]
+prizer	1.0	1.0	[0, 3, 0, 0, 2, 1, 2, 1, 0, 1]
+prizers	0.8	0.9798	[2, 0, 0, 1, 3, 1, 0, 1, 0, 0]
+prizes	2.0	1.09545	[3, 3, 2, 0, 2, 1, 2, 4, 1, 2]
+prizewinner	2.3	1.00499	[3, 0, 3, 3, 2, 2, 2, 4, 2, 2]
+prizewinners	2.4	1.11355	[4, 2, 2, 2, 0, 4, 2, 3, 3, 2]
+prizewinning	3.0	0.7746	[3, 3, 3, 3, 3, 4, 3, 1, 3, 4]
+proactive	1.8	0.87178	[2, 3, 3, 1, 1, 1, 1, 3, 1, 2]
+problem	-1.7	0.64031	[-2, -2, -1, -1, -1, -3, -1, -2, -2, -2]
+problematic	-1.9	0.53852	[-1, -2, -2, -2, -2, -3, -2, -1, -2, -2]
+problematical	-1.8	0.6	[-3, -1, -1, -2, -2, -2, -2, -2, -1, -2]
+problematically	-2.0	1.0	[-2, -1, -3, -1, -1, -2, -4, -3, -1, -2]
+problematics	-1.3	1.1	[0, -1, -1, 0, -2, -1, -4, -1, -2, -1]
+problems	-1.7	0.78102	[-2, -1, -1, -3, -2, -1, -3, -1, -1, -2]
+profit	1.9	0.7	[2, 3, 2, 1, 2, 1, 3, 1, 2, 2]
+profitabilities	1.1	0.7	[1, 1, 3, 1, 1, 1, 1, 0, 1, 1]
+profitability	1.1	1.44568	[1, 1, -2, 2, 0, 3, 1, 3, 2, 0]
+profitable	1.9	0.9434	[2, 3, 0, 3, 1, 2, 1, 3, 2, 2]
+profitableness	2.4	1.11355	[1, 4, 2, 4, 2, 2, 4, 2, 1, 2]
+profitably	1.6	0.91652	[1, 2, 0, 3, 1, 3, 1, 1, 2, 2]
+profited	1.3	1.00499	[2, 2, 2, 1, 0, 0, 1, 3, 0, 2]
+profiteer	0.8	1.6	[2, -2, -1, 3, -1, 2, 1, 2, 0, 2]
+profiteered	-0.5	1.9105	[0, 0, 2, -2, -3, -2, 3, 0, -3, 0]
+profiteering	-0.6	2.05913	[-1, 2, -2, -4, -2, 2, 1, -2, 2, -2]
+profiteers	0.5	1.5	[-2, 1, -1, -1, 1, -1, 2, 2, 2, 2]
+profiter	0.7	1.55242	[2, 2, 2, 1, -1, 1, -1, 3, 0, -2]
+profiterole	0.4	0.66332	[0, 0, 0, 0, 0, 1, 0, 1, 2, 0]
+profiteroles	0.5	0.92195	[0, 0, -1, 2, 2, 0, 0, 1, 0, 1]
+profiting	1.6	0.91652	[1, 0, 3, 2, 1, 2, 3, 1, 1, 2]
+profitless	-1.5	0.92195	[-2, -2, -3, -1, -1, -1, 0, -1, -1, -3]
+profits	1.9	1.04403	[2, 2, 1, 0, 2, 1, 2, 4, 3, 2]
+profitwise	0.9	0.83066	[1, 2, 0, 0, 1, 2, 2, 0, 1, 0]
+progress	1.8	0.74833	[3, 2, 1, 2, 3, 1, 1, 2, 2, 1]
+prominent	1.3	0.45826	[2, 1, 1, 2, 1, 1, 1, 2, 1, 1]
+promiscuities	-0.8	1.32665	[-1, 0, -2, -2, -1, 2, -3, -1, 0, 0]
+promiscuity	-1.8	1.07703	[-1, -2, -4, -2, -3, -1, 0, -2, -1, -2]
+promiscuous	-0.3	1.34536	[2, -3, -1, -1, 0, -1, 0, -1, 1, 1]
+promiscuously	-1.5	1.28452	[-2, -1, -3, 2, -2, -2, -1, -2, -2, -2]
+promiscuousness	-0.9	1.37477	[-3, -1, 1, -2, -2, 1, 1, -1, -2, -1]
+promise	1.3	0.64031	[1, 0, 1, 1, 2, 2, 1, 1, 2, 2]
+promised	1.5	0.92195	[2, 1, 1, 0, 0, 2, 2, 3, 2, 2]
+promisee	0.8	0.87178	[2, 1, 0, 0, 0, 2, 0, 2, 1, 0]
+promisees	1.1	0.9434	[2, 0, 1, 0, 0, 0, 2, 2, 2, 2]
+promiser	1.3	0.9	[2, 1, 1, 0, 0, 2, 2, 3, 1, 1]
+promisers	1.6	0.4899	[2, 1, 2, 1, 2, 1, 2, 1, 2, 2]
+promises	1.6	0.8	[2, 1, 1, 0, 2, 1, 3, 2, 2, 2]
+promising	1.7	0.45826	[1, 2, 2, 1, 2, 2, 1, 2, 2, 2]
+promisingly	1.2	0.6	[2, 2, 1, 1, 1, 2, 1, 0, 1, 1]
+promisor	1.0	0.63246	[2, 2, 0, 1, 1, 1, 0, 1, 1, 1]
+promisors	0.4	0.8	[0, 0, 0, 2, 0, 2, 0, 0, 0, 0]
+promissory	0.9	1.13578	[2, 0, 0, 3, 0, 2, 2, 0, 0, 0]
+promote	1.6	0.8	[2, 1, 2, 3, 0, 1, 2, 2, 1, 2]
+promoted	1.8	0.74833	[2, 2, 1, 1, 1, 2, 2, 1, 3, 3]
+promotes	1.4	0.91652	[1, 2, 0, 0, 1, 2, 2, 1, 3, 2]
+promoting	1.5	0.67082	[1, 2, 2, 1, 2, 1, 2, 0, 2, 2]
+propaganda	-1.0	1.54919	[-2, -3, -2, -3, -2, 1, -1, 1, 0, 1]
+prosecute	-1.7	1.00499	[-2, -2, -2, -1, -1, -2, 0, -1, -4, -2]
+prosecuted	-1.6	1.95959	[-2, -2, -2, -3, -3, -3, -4, 2, 2, -1]
+prosecutes	-1.8	1.53623	[-2, -2, -2, -3, -2, -2, -4, 1, 1, -3]
+prosecution	-2.2	1.07703	[-4, -1, -2, -2, -3, -2, -1, -4, -1, -2]
+prospect	1.2	0.87178	[1, 3, 1, 0, 2, 2, 1, 0, 1, 1]
+prospects	1.2	0.6	[2, 1, 1, 1, 1, 0, 1, 2, 2, 1]
+prosperous	2.1	1.86815	[-3, 3, 3, 2, 4, 2, 3, 3, 3, 1]
+protect	1.6	0.8	[1, 3, 1, 1, 1, 1, 3, 2, 1, 2]
+protected	1.9	0.7	[1, 1, 2, 3, 2, 2, 2, 1, 3, 2]
+protects	1.3	0.78102	[2, 2, 0, 2, 1, 1, 0, 2, 2, 1]
+protest	-1.0	1.34164	[-2, -1, -1, -2, -1, -2, 1, -2, 2, -2]
+protested	-0.5	1.62788	[-2, -3, -1, -1, 0, 2, 2, -2, 1, -1]
+protesters	-0.9	0.7	[0, 0, 0, -1, -2, -2, -1, -1, -1, -1]
+protesting	-1.8	0.74833	[-2, -2, -1, -2, -1, -1, -2, -1, -3, -3]
+protests	-0.9	1.57797	[-2, -2, 2, 0, -1, -2, -2, -2, 2, -2]
+proud	2.1	0.3	[2, 3, 2, 2, 2, 2, 2, 2, 2, 2]
+prouder	2.2	1.16619	[2, 3, 3, 4, 0, 1, 1, 3, 2, 3]
+proudest	2.6	0.66332	[4, 2, 2, 2, 2, 3, 2, 3, 3, 3]
+proudful	1.9	1.51327	[3, 3, 0, 1, -1, 1, 4, 3, 2, 3]
+proudhearted	1.4	0.91652	[2, -1, 1, 2, 2, 1, 2, 2, 2, 1]
+proudly	2.6	0.4899	[2, 2, 3, 3, 2, 3, 3, 3, 2, 3]
+provoke	-1.7	0.64031	[-2, -2, -1, -1, -1, -2, -2, -1, -3, -2]
+provoked	-1.1	0.83066	[-1, -1, 0, -2, -2, -2, -2, 0, 0, -1]
+provokes	-1.3	0.78102	[-2, -2, -1, -2, -1, -2, -2, 0, 0, -1]
+provoking	-0.8	1.249	[-2, -2, -1, -2, 1, -1, 1, 1, -1, -2]
+pseudoscience	-1.2	1.32665	[-1, -1, -3, -4, 0, 0, -2, 0, 0, -1]
+puke	-2.4	1.0198	[-1, -3, -3, -2, -4, -4, -2, -1, -2, -2]
+puked	-1.8	0.6	[-1, -2, -2, -3, -1, -1, -2, -2, -2, -2]
+pukes	-1.9	0.7	[-1, -2, -3, -3, -1, -1, -2, -2, -2, -2]
+puking	-1.8	1.46969	[0, -2, -4, -3, -2, -3, 1, -1, -1, -3]
+pukka	2.8	0.4	[3, 2, 3, 3, 3, 2, 3, 3, 3, 3]
+punish	-2.4	0.91652	[-1, -3, -3, -4, -3, -1, -2, -2, -2, -3]
+punishabilities	-1.7	0.78102	[0, -2, -3, -2, -1, -2, -2, -1, -2, -2]
+punishability	-1.6	1.49666	[-2, -2, -1, -1, -2, -2, -3, 2, -4, -1]
+punishable	-1.9	0.7	[-3, -1, -1, -2, -2, -1, -3, -2, -2, -2]
+punished	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -2, -3, -2]
+punisher	-1.9	0.53852	[-3, -1, -2, -2, -2, -2, -2, -1, -2, -2]
+punishers	-2.6	0.8	[-3, -3, -3, -3, -2, -2, -4, -2, -1, -3]
+punishes	-2.1	0.7	[-3, -2, -3, -2, -1, -2, -2, -3, -1, -2]
+punishing	-2.6	0.8	[-2, -3, -3, -3, -4, -1, -3, -2, -2, -3]
+punishment	-2.2	0.6	[-2, -1, -2, -2, -3, -3, -2, -2, -2, -3]
+punishments	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -2, -3, -1, -2]
+punitive	-2.3	0.78102	[-4, -2, -3, -1, -2, -2, -2, -2, -3, -2]
+pushy	-1.1	0.83066	[-2, -2, -1, -1, -1, 1, -1, -2, -1, -1]
+puzzled	-0.7	0.45826	[0, 0, -1, -1, 0, -1, -1, -1, -1, -1]
+quaking	-1.5	0.67082	[-1, -2, -2, -2, -1, 0, -2, -1, -2, -2]
+questionable	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+questioned	-0.4	1.0198	[-2, 0, 0, -1, -1, 2, 0, 0, -1, -1]
+questioning	-0.4	0.66332	[0, -1, -1, 0, 0, 0, -2, 0, 0, 0]
+racism	-3.1	0.9434	[-4, -4, -4, -2, -3, -4, -2, -2, -2, -4]
+racist	-3.0	0.89443	[-1, -3, -3, -4, -3, -4, -4, -2, -3, -3]
+racists	-2.5	0.92195	[-3, 0, -3, -2, -2, -3, -3, -3, -3, -3]
+radian	0.4	0.66332	[0, 0, 0, 0, 0, 0, 1, 2, 0, 1]
+radiance	1.4	1.11355	[3, 1, 2, 3, 1, 1, -1, 1, 2, 1]
+radiances	1.1	0.53852	[1, 2, 2, 1, 1, 1, 0, 1, 1, 1]
+radiancies	0.8	1.16619	[-1, 0, 3, 1, 1, 1, 1, 2, -1, 1]
+radiancy	1.4	0.66332	[2, 1, 1, 3, 1, 1, 1, 1, 2, 1]
+radians	0.2	0.6	[0, 2, 0, 0, 0, 0, 0, 0, 0, 0]
+radiant	2.1	0.83066	[4, 2, 2, 2, 2, 1, 1, 3, 2, 2]
+radiantly	1.3	0.78102	[3, 2, 1, 1, 1, 1, 1, 0, 1, 2]
+radiants	1.2	0.6	[2, 1, 0, 2, 1, 1, 1, 2, 1, 1]
+rage	-2.6	0.8	[-3, -2, -2, -3, -3, -4, -1, -2, -3, -3]
+raged	-2.0	0.63246	[-2, -1, -1, -3, -3, -2, -2, -2, -2, -2]
+ragee	-0.4	1.42829	[-2, -1, 0, 3, 0, -2, -2, 0, 0, 0]
+rageful	-2.8	0.6	[-3, -3, -3, -3, -2, -4, -2, -3, -2, -3]
+rages	-2.1	0.7	[-3, -1, -1, -3, -3, -2, -2, -2, -2, -2]
+raging	-2.4	1.0198	[-1, -3, -3, -1, -3, -3, -1, -4, -2, -3]
+rainy	-0.3	0.64031	[-1, 0, 1, 0, 0, 0, -1, 0, -1, -1]
+rancid	-2.5	1.11803	[-3, -3, -3, -2, -3, 0, -3, -1, -4, -3]
+rancidity	-2.6	0.8	[-4, -3, -3, -2, -2, -2, -2, -2, -2, -4]
+rancidly	-2.5	1.20416	[-2, -1, -4, -3, -4, -1, -2, -3, -4, -1]
+rancidness	-2.6	0.91652	[-3, -4, -2, -3, -4, -2, -3, -1, -2, -2]
+rancidnesses	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -2, -1, -2]
+rant	-1.4	0.66332	[-1, -2, -2, -1, -2, -2, -2, -1, 0, -1]
+ranter	-1.2	1.16619	[-1, -2, -2, -2, -1, -1, -1, -2, 2, -2]
+ranters	-1.2	0.87178	[-1, -1, -1, 0, -1, -1, -3, -2, 0, -2]
+rants	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -1, -2, -2, -1]
+rape	-3.7	0.64031	[-4, -2, -4, -4, -4, -4, -4, -4, -3, -4]
+raped	-3.6	0.4899	[-3, -3, -4, -4, -3, -4, -4, -4, -3, -4]
+raper	-3.4	0.66332	[-3, -3, -4, -4, -3, -3, -4, -4, -2, -4]
+rapers	-3.6	0.66332	[-2, -4, -4, -3, -4, -3, -4, -4, -4, -4]
+rapes	-3.5	0.67082	[-4, -3, -4, -4, -3, -4, -4, -3, -2, -4]
+rapeseeds	-0.5	1.20416	[0, 0, 0, 0, 0, -4, 0, 0, -1, 0]
+raping	-3.8	0.4	[-3, -4, -4, -4, -4, -4, -4, -4, -3, -4]
+rapist	-3.9	0.3	[-4, -4, -4, -4, -4, -4, -3, -4, -4, -4]
+rapists	-3.3	0.64031	[-3, -3, -4, -3, -4, -3, -4, -2, -4, -3]
+rapture	0.6	2.2891	[-2, 2, -2, 3, 3, 4, -1, -1, 2, -2]
+raptured	0.9	1.97231	[0, -2, 0, 2, 4, -1, 4, -1, 1, 2]
+raptures	0.7	2.05183	[0, -2, 0, 2, 4, -2, 4, -1, 1, 1]
+rapturous	1.7	1.95192	[3, 4, 0, 3, 2, 2, 4, -2, -1, 2]
+rash	-1.7	0.78102	[-2, -1, -1, -3, -2, -2, -1, -1, -1, -3]
+ratified	0.6	0.4899	[1, 0, 0, 1, 1, 0, 1, 1, 0, 1]
+reach	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
+reached	0.4	0.4899	[1, 0, 0, 0, 1, 1, 0, 1, 0, 0]
+reaches	0.2	0.4	[0, 0, 0, 1, 0, 1, 0, 0, 0, 0]
+reaching	0.8	0.6	[1, 0, 2, 0, 1, 0, 1, 1, 1, 1]
+readiness	1.0	0.63246	[1, 1, 1, 1, 0, 1, 2, 1, 2, 0]
+ready	1.5	1.0247	[2, 1, 1, 0, 2, 2, 1, 1, 1, 4]
+reassurance	1.5	0.5	[1, 1, 1, 1, 2, 1, 2, 2, 2, 2]
+reassurances	1.4	0.8	[0, 1, 1, 2, 1, 1, 1, 2, 3, 2]
+reassure	1.4	0.4899	[2, 2, 1, 1, 2, 1, 2, 1, 1, 1]
+reassured	1.7	0.45826	[2, 1, 1, 1, 2, 2, 2, 2, 2, 2]
+reassures	1.5	0.92195	[2, 1, 1, 2, 2, 2, -1, 2, 2, 2]
+reassuring	1.7	1.48661	[3, 3, 2, -2, 1, 3, 3, 2, 1, 1]
+reassuringly	1.8	0.87178	[1, 3, 2, 1, 2, 3, 3, 1, 1, 1]
+rebel	-0.6	1.49666	[-2, -1, -1, 0, -2, -1, 2, 1, 1, -3]
+rebeldom	-1.5	1.0247	[-2, -2, -1, -3, -2, -2, -1, 1, -1, -2]
+rebelled	-1.0	1.26491	[-2, -2, 0, -2, 0, -2, -2, -1, -1, 2]
+rebelling	-1.1	1.51327	[-3, -1, -2, -1, -2, -1, -1, -3, 2, 1]
+rebellion	-0.5	1.80278	[-2, -2, -1, -1, 3, -1, 1, -3, 2, -1]
+rebellions	-1.1	1.57797	[-2, -4, -3, 0, 0, -1, 1, -2, -1, 1]
+rebellious	-1.2	1.249	[-2, -1, -3, -1, -2, -2, 1, -1, 1, -2]
+rebelliously	-1.8	0.87178	[-3, 0, -2, -2, -1, -2, -3, -1, -2, -2]
+rebelliousness	-1.2	1.16619	[0, -3, -1, -2, 1, -1, -2, 0, -2, -2]
+rebels	-0.8	1.07703	[-1, 0, 0, -2, 0, -3, 0, 0, 0, -2]
+recession	-1.8	1.07703	[-3, -1, -4, -2, -1, -1, -1, -1, -3, -1]
+reckless	-1.7	0.64031	[-2, -1, -1, -3, -1, -2, -1, -2, -2, -2]
+recommend	1.5	0.67082	[1, 1, 1, 1, 2, 3, 2, 2, 1, 1]
+recommended	0.8	1.07703	[1, 1, 0, -2, 1, 2, 1, 2, 1, 1]
+recommends	0.9	0.9434	[1, 1, 2, 0, 0, 2, 1, -1, 2, 1]
+redeemed	1.3	0.9	[2, 1, 2, 2, 1, -1, 2, 1, 2, 1]
+reek	-2.4	0.66332	[-3, -3, -2, -3, -3, -2, -2, -2, -1, -3]
+reeked	-2.0	1.09545	[-4, -3, -2, -3, -1, -2, 0, -1, -2, -2]
+reeker	-1.7	1.1	[0, -2, -1, 0, -3, -3, -2, -1, -3, -2]
+reekers	-1.5	1.0247	[-3, 0, 0, 0, -2, -2, -2, -2, -2, -2]
+reeking	-2.0	1.48324	[2, -2, -2, -3, -3, -3, -1, -3, -3, -2]
+refuse	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+refused	-1.2	0.74833	[0, -1, -1, -1, -1, -1, -2, -1, -3, -1]
+refusing	-1.7	0.64031	[-1, -1, -1, -2, -2, -2, -3, -1, -2, -2]
+regret	-1.8	0.6	[-2, -2, -2, -2, -1, -3, -1, -1, -2, -2]
+regretful	-1.9	0.83066	[-1, -2, -1, -2, -1, -2, -1, -3, -3, -3]
+regretfully	-1.9	0.83066	[-1, -1, -1, -3, -2, -3, -1, -3, -2, -2]
+regretfulness	-1.6	0.66332	[-1, -3, -1, -1, -1, -2, -1, -2, -2, -2]
+regrets	-1.5	0.5	[-2, -2, -2, -1, -2, -1, -1, -2, -1, -1]
+regrettable	-2.3	0.78102	[-3, -1, -2, -1, -3, -2, -3, -3, -2, -3]
+regrettably	-2.0	0.63246	[-2, -3, -1, -3, -2, -1, -2, -2, -2, -2]
+regretted	-1.6	0.4899	[-2, -1, -2, -2, -2, -2, -1, -1, -1, -2]
+regretter	-1.6	0.66332	[-2, -1, -2, -2, -3, -2, -1, -1, -1, -1]
+regretters	-2.0	0.89443	[-1, -2, -2, -2, -4, -3, -1, -1, -2, -2]
+regretting	-1.7	0.78102	[-3, -2, -2, -1, -3, -1, -1, -1, -2, -1]
+reinvigorate	2.3	0.78102	[3, 3, 3, 2, 3, 1, 2, 1, 2, 3]
+reinvigorated	1.9	1.13578	[2, 2, 3, 1, 2, 3, 3, -1, 2, 2]
+reinvigorates	1.8	0.9798	[2, 2, 3, 0, 2, 2, 3, 0, 2, 2]
+reinvigorating	1.7	0.64031	[1, 2, 1, 1, 2, 2, 2, 1, 3, 2]
+reinvigoration	2.2	0.4	[2, 2, 2, 3, 2, 3, 2, 2, 2, 2]
+reject	-1.7	0.64031	[-1, -2, -2, -2, -1, -3, -1, -1, -2, -2]
+rejected	-2.3	0.45826	[-3, -2, -3, -3, -2, -2, -2, -2, -2, -2]
+rejectee	-2.3	0.45826	[-3, -2, -2, -3, -2, -3, -2, -2, -2, -2]
+rejectees	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -2, -2, -1]
+rejecter	-1.6	0.66332	[-2, -1, -1, -3, -2, -2, -1, -1, -1, -2]
+rejecters	-1.8	0.6	[-2, -3, -1, -1, -2, -1, -2, -2, -2, -2]
+rejecting	-2.0	0.7746	[-1, -2, -3, -1, -2, -3, -2, -1, -3, -2]
+rejectingly	-1.7	0.64031	[-1, -2, -2, -2, -1, -2, -2, -1, -3, -1]
+rejection	-2.5	0.67082	[-3, -3, -2, -4, -3, -2, -2, -2, -2, -2]
+rejections	-2.1	0.53852	[-3, -2, -2, -2, -1, -2, -3, -2, -2, -2]
+rejective	-1.8	0.6	[-3, -2, -2, -2, -1, -1, -2, -2, -1, -2]
+rejector	-1.8	0.74833	[-2, -1, -2, -3, -1, -2, -1, -2, -3, -1]
+rejects	-2.2	0.4	[-3, -2, -2, -2, -2, -3, -2, -2, -2, -2]
+rejoice	1.9	0.9434	[2, 3, 1, 3, 1, 3, 1, 3, 1, 1]
+rejoiced	2.0	0.63246	[2, 1, 2, 3, 2, 2, 3, 1, 2, 2]
+rejoices	2.1	0.7	[2, 1, 2, 3, 2, 3, 3, 2, 2, 1]
+rejoicing	2.8	0.4	[3, 3, 2, 3, 3, 3, 2, 3, 3, 3]
+relax	1.9	1.13578	[2, 1, 1, 1, 4, 4, 2, 1, 1, 2]
+relaxant	1.0	0.89443	[2, 1, 0, 0, 1, 0, 1, 3, 1, 1]
+relaxants	0.7	0.9	[0, 1, 1, 0, -1, 2, 1, 2, 1, 0]
+relaxation	2.4	0.4899	[3, 2, 3, 2, 2, 3, 3, 2, 2, 2]
+relaxations	1.0	0.89443	[-1, 0, 2, 1, 1, 2, 1, 2, 1, 1]
+relaxed	2.2	0.87178	[2, 3, 1, 3, 3, 3, 1, 2, 1, 3]
+relaxedly	1.5	0.5	[2, 2, 1, 1, 2, 1, 2, 2, 1, 1]
+relaxedness	2.0	0.63246	[2, 2, 3, 1, 3, 2, 2, 2, 1, 2]
+relaxer	1.6	0.8	[0, 2, 1, 2, 1, 3, 1, 2, 2, 2]
+relaxers	1.4	0.4899	[2, 1, 1, 1, 2, 2, 2, 1, 1, 1]
+relaxes	1.5	0.5	[2, 1, 1, 1, 1, 2, 2, 2, 1, 2]
+relaxin	1.7	0.64031	[2, 2, 1, 2, 0, 2, 2, 2, 2, 2]
+relaxing	2.2	0.6	[1, 2, 2, 2, 2, 3, 3, 3, 2, 2]
+relaxins	1.2	1.4	[1, 3, 2, 1, 0, 1, -2, 3, 2, 1]
+relentless	0.2	1.07703	[3, -1, 0, -1, 0, 1, 0, 0, 0, 0]
+reliant	0.5	1.20416	[0, 2, -1, 1, 0, 1, 2, -1, 2, -1]
+relief	2.1	0.53852	[2, 2, 2, 3, 2, 3, 2, 1, 2, 2]
+reliefs	1.3	0.78102	[1, 2, 2, 2, 2, 2, 0, 0, 1, 1]
+relievable	1.1	1.22066	[1, -2, 1, 1, 1, 1, 3, 2, 1, 2]
+relieve	1.5	0.5	[1, 2, 1, 2, 1, 1, 2, 2, 1, 2]
+relieved	1.6	0.66332	[2, 1, 2, 1, 1, 3, 2, 1, 1, 2]
+relievedly	1.4	0.4899	[1, 2, 1, 1, 1, 2, 2, 2, 1, 1]
+reliever	1.5	0.80623	[2, 1, 2, 2, 1, 2, 0, 1, 1, 3]
+relievers	1.0	0.63246	[1, 1, 1, 1, 2, 0, 2, 0, 1, 1]
+relieves	1.5	0.80623	[2, 1, 2, 2, 1, 2, 0, 1, 1, 3]
+relieving	1.5	1.0247	[2, 2, 1, 2, 3, -1, 2, 1, 1, 2]
+relievo	1.3	1.00499	[0, 2, 1, 2, 2, -1, 2, 2, 2, 1]
+relishing	1.6	0.8	[1, 2, 1, 3, 2, 3, 1, 1, 1, 1]
+reluctance	-1.4	0.4899	[-2, -2, -1, -1, -1, -1, -2, -1, -2, -1]
+reluctancy	-1.6	0.8	[-3, -2, -1, -1, -1, -1, -2, -1, -3, -1]
+reluctant	-1.0	0.7746	[0, -1, 0, -1, -1, 0, -1, -2, -2, -2]
+reluctantly	-0.4	1.42829	[-1, 2, -1, -2, -2, -1, 1, -1, 2, -1]
+remarkable	2.6	1.0198	[3, 4, 3, 2, 2, 3, 3, 0, 3, 3]
+remorse	-1.1	1.51327	[-3, -1, -3, 1, 2, -2, -1, -1, -2, -1]
+remorseful	-0.9	2.07123	[-1, 1, -2, -3, 2, -1, -3, -2, 3, -3]
+remorsefully	-0.7	1.34536	[-1, -1, 0, -1, -2, -1, -1, 1, -3, 2]
+remorsefulness	-0.7	1.61555	[-1, -2, 2, -2, -2, -1, 0, -3, 2, 0]
+remorseless	-2.3	0.64031	[-4, -2, -2, -2, -3, -2, -2, -2, -2, -2]
+remorselessly	-2.0	1.09545	[-3, -3, -3, -2, -1, -1, -4, -1, -1, -1]
+remorselessness	-2.8	1.16619	[-3, -4, -2, -2, -3, -4, -1, -1, -4, -4]
+repetitive	-1.0	0.06325	[-1, -1, 0, -2, -1, -2, -1, -1, 0, -1]
+repress	-1.4	0.66332	[-1, -1, -3, -2, -1, -1, -2, -1, -1, -1]
+repressed	-1.3	0.78102	[-1, 0, -3, -1, -1, -2, -1, -1, -2, -1]
+represses	-1.3	1.00499	[-1, 0, -3, -1, 0, -3, -1, -1, -2, -1]
+repressible	-1.5	0.92195	[-1, -2, -3, -1, 0, -1, -3, -1, -2, -1]
+repressing	-1.8	0.6	[-1, -2, -2, -2, -1, -3, -2, -1, -2, -2]
+repression	-1.6	0.91652	[-2, -2, -1, -1, -1, -1, -4, -1, -2, -1]
+repressions	-1.7	1.00499	[-2, -3, -1, -2, -2, -3, -2, 0, 0, -2]
+repressive	-1.4	1.11355	[-3, -1, -1, -2, -1, -3, 1, -2, -1, -1]
+repressively	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -2, -2, -1, -1]
+repressiveness	-1.0	1.73205	[-2, -1, -2, -3, -1, -1, 1, -3, 3, -1]
+repressor	-1.4	1.28062	[-1, 0, -3, -1, -2, -4, 0, -1, 0, -2]
+repressors	-2.2	1.66132	[-2, -4, 0, -2, -1, -3, -4, -3, 1, -4]
+repressurize	-0.3	0.64031	[0, 0, 0, 0, 0, 0, -2, 0, -1, 0]
+repressurized	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+repressurizes	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+repressurizing	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+repulse	-2.8	0.4	[-3, -3, -3, -3, -2, -3, -3, -3, -2, -3]
+repulsed	-2.2	0.9798	[0, -2, -2, -2, -3, -3, -1, -3, -3, -3]
+rescue	2.3	0.78102	[1, 3, 1, 3, 2, 3, 3, 2, 2, 3]
+rescued	1.8	1.53623	[3, 2, 2, -2, 3, 2, 1, 4, 1, 2]
+rescues	1.3	0.78102	[3, 2, 0, 2, 1, 1, 1, 1, 1, 1]
+resent	-0.7	1.26886	[-2, -2, 0, -1, -1, -1, -2, 1, 2, -1]
+resented	-1.6	1.35647	[-2, -3, -2, -2, -1, -1, 2, -3, -2, -2]
+resentence	-1.0	0.7746	[-1, 0, -1, -1, 0, -2, -1, 0, -2, -2]
+resentenced	-0.8	0.9798	[0, -2, -1, 0, -1, 0, 0, 0, -3, -1]
+resentences	-0.6	0.8	[0, -2, -1, 0, -1, 0, 0, 0, -2, 0]
+resentencing	0.2	0.87178	[-1, -1, 0, 1, 0, 0, 1, 2, 0, 0]
+resentful	-2.1	0.83066	[-3, -1, -2, -3, -1, -1, -3, -2, -2, -3]
+resentfully	-1.4	1.11355	[-1, -2, -1, -1, -3, 1, -1, -3, -1, -2]
+resentfulness	-2.0	0.7746	[-2, -2, -3, -3, -2, -3, -2, -1, -1, -1]
+resenting	-1.2	1.72047	[-2, -1, -2, -2, -1, -3, -3, 2, 2, -2]
+resentment	-1.9	0.83066	[-1, -3, -2, -3, -2, -3, -1, -1, -1, -2]
+resentments	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -2, -2, -1, -3]
+resents	-1.2	1.32665	[-2, -1, -1, -3, 1, -1, 1, -3, -2, -1]
+resign	-1.4	0.66332	[-2, -1, -3, -1, -1, -1, -1, -2, -1, -1]
+resignation	-1.2	0.4	[-1, -1, -1, -2, -1, -1, -1, -1, -2, -1]
+resignations	-1.2	0.6	[0, -1, -1, -2, -2, -2, -1, -1, -1, -1]
+resigned	-1.0	0.63246	[-2, -1, 0, -1, -2, -1, -1, -1, 0, -1]
+resignedly	-0.7	1.26886	[-3, -1, -1, -1, -1, 1, 1, 1, -2, -1]
+resignedness	-0.8	1.07703	[-1, -2, 1, -2, -1, -1, 0, -2, -1, 1]
+resigner	-1.2	0.6	[-2, -1, 0, -1, -2, -2, -1, -1, -1, -1]
+resigners	-1.0	1.09545	[-1, 0, -1, -3, -1, 0, 0, -1, -3, 0]
+resigning	-0.9	1.22066	[-1, -1, -1, -1, -1, 0, -1, -3, -2, 2]
+resigns	-1.3	0.9	[0, -1, -1, 0, -2, -1, -3, -1, -2, -2]
+resolute	1.1	0.53852	[2, 1, 0, 1, 1, 1, 2, 1, 1, 1]
+resolvable	1.0	0.0	[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+resolve	1.6	0.66332	[2, 1, 1, 2, 2, 1, 3, 1, 1, 2]
+resolved	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
+resolvent	0.7	0.78102	[1, 0, 1, 2, 0, -1, 1, 1, 1, 1]
+resolvents	0.4	0.66332	[2, 0, 0, 1, 0, 0, 1, 0, 0, 0]
+resolver	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
+resolvers	1.4	0.4899	[2, 1, 2, 1, 1, 1, 2, 1, 2, 1]
+resolves	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
+resolving	1.6	0.4899	[2, 2, 1, 2, 2, 1, 1, 1, 2, 2]
+respect	2.1	0.53852	[2, 2, 2, 2, 3, 3, 2, 2, 1, 2]
+respectabilities	1.8	0.4	[2, 2, 2, 1, 2, 2, 2, 1, 2, 2]
+respectability	2.4	0.8	[4, 1, 3, 2, 3, 3, 2, 2, 2, 2]
+respectable	1.9	0.7	[2, 2, 2, 2, 1, 3, 3, 1, 1, 2]
+respectableness	1.2	1.32665	[2, 1, 1, 0, 3, 2, -2, 2, 2, 1]
+respectably	1.7	0.78102	[2, 2, 1, 3, 1, 3, 2, 1, 1, 1]
+respected	2.1	0.7	[2, 2, 1, 2, 3, 1, 2, 3, 3, 2]
+respecter	2.1	0.53852	[3, 2, 2, 2, 2, 2, 1, 3, 2, 2]
+respecters	1.6	0.8	[2, 1, 2, 2, 3, 1, 2, 2, 0, 1]
+respectful	2.0	0.7746	[1, 1, 3, 2, 2, 3, 1, 2, 3, 2]
+respectfully	1.7	0.64031	[1, 2, 1, 2, 2, 2, 1, 3, 1, 2]
+respectfulness	1.9	1.37477	[4, 2, 2, 1, 2, 4, -1, 1, 2, 2]
+respectfulnesses	1.3	1.18743	[1, 1, 2, 2, 2, 2, 2, 1, -2, 2]
+respecting	2.2	0.6	[1, 3, 2, 3, 2, 2, 3, 2, 2, 2]
+respective	1.8	1.16619	[2, 2, 3, 0, 1, 3, 3, 1, 0, 3]
+respectively	1.4	0.91652	[0, 0, 2, 2, 0, 2, 2, 2, 2, 2]
+respectiveness	1.1	1.04403	[0, 2, 1, 0, 1, 0, 2, 2, 0, 3]
+respects	1.3	1.00499	[2, 0, 0, 0, 2, 1, 2, 1, 2, 3]
+responsible	1.3	1.1	[1, 1, 0, 4, 2, 2, 1, 0, 1, 1]
+responsive	1.5	0.92195	[3, 1, 1, 0, 1, 1, 2, 3, 2, 1]
+restful	1.5	0.67082	[1, 1, 1, 1, 2, 1, 2, 1, 2, 3]
+restless	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -1]
+restlessly	-1.4	0.91652	[-1, -4, -1, -1, -1, -2, -1, -1, -1, -1]
+restlessness	-1.2	0.74833	[-3, -1, -1, 0, -1, -2, -1, -1, -1, -1]
+restore	1.2	0.9798	[1, 1, 2, 2, 2, 2, 1, -1, 0, 2]
+restored	1.4	0.91652	[2, 2, 1, 2, 1, 2, 2, 1, -1, 2]
+restores	1.2	0.6	[2, 1, 1, 2, 1, 0, 1, 1, 2, 1]
+restoring	1.2	0.4	[2, 1, 1, 1, 1, 2, 1, 1, 1, 1]
+restrict	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -2, -1, -1, -2]
+restricted	-1.6	0.4899	[-1, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+restricting	-1.6	0.4899	[-2, -2, -2, -2, -1, -2, -1, -1, -2, -1]
+restriction	-1.1	0.9434	[-1, -1, -1, -1, -3, 1, -2, -1, -1, -1]
+restricts	-1.3	1.1	[-2, -2, -3, -1, -1, -2, 1, -1, -2, 0]
+retained	0.1	0.7	[-1, 1, 1, 1, 0, -1, 0, 0, 0, 0]
+retard	-2.4	0.8	[-2, -2, -2, -1, -3, -2, -4, -3, -3, -2]
+retarded	-2.7	1.26886	[-4, -1, -3, -3, -4, -4, -2, -1, -1, -4]
+retreat	0.8	1.07703	[2, 2, 0, 0, -1, 1, 2, 0, 2, 0]
+revenge	-2.4	0.66332	[-2, -3, -2, -3, -3, -3, -2, -1, -2, -3]
+revenged	-0.9	1.37477	[-2, -3, -2, -1, -1, 2, -1, 1, -1, -1]
+revengeful	-2.4	0.4899	[-2, -2, -2, -3, -3, -2, -3, -3, -2, -2]
+revengefully	-1.4	2.00998	[-3, -2, -2, -2, 3, 2, -3, -3, -2, -2]
+revengefulness	-2.2	0.87178	[-2, -3, -3, -2, -2, -2, -1, -4, -1, -2]
+revenger	-2.1	0.83066	[-2, -3, -2, -1, -1, -2, -3, -3, -1, -3]
+revengers	-2.0	0.44721	[-2, -2, -3, -2, -2, -2, -1, -2, -2, -2]
+revenges	-1.9	0.7	[-2, -3, -2, -1, -1, -2, -3, -2, -1, -2]
+revered	2.3	1.1	[3, 3, 1, 3, 3, 3, 0, 3, 3, 1]
+revive	1.4	1.11355	[4, 0, 2, 1, 1, 0, 2, 2, 1, 1]
+revives	1.6	0.4899	[1, 1, 2, 2, 1, 2, 2, 2, 1, 2]
+reward	2.7	0.78102	[3, 4, 1, 2, 3, 3, 2, 3, 3, 3]
+rewardable	2.0	1.0	[3, 1, 4, 3, 1, 2, 1, 2, 2, 1]
+rewarded	2.2	0.74833	[1, 2, 3, 2, 2, 4, 2, 2, 2, 2]
+rewarder	1.6	0.8	[1, 2, 3, 1, 1, 3, 2, 1, 1, 1]
+rewarders	1.9	0.83066	[1, 2, 2, 1, 3, 3, 1, 2, 1, 3]
+rewarding	2.4	0.8	[3, 4, 2, 2, 1, 3, 3, 2, 2, 2]
+rewardingly	2.4	0.8	[3, 2, 3, 4, 3, 2, 2, 2, 1, 2]
+rewards	2.1	0.83066	[2, 1, 3, 4, 2, 2, 2, 2, 1, 2]
+rich	2.6	0.8	[2, 3, 2, 4, 4, 3, 2, 2, 2, 2]
+richened	1.9	0.83066	[3, 2, 2, 1, 3, 1, 2, 3, 1, 1]
+richening	1.0	1.34164	[2, 2, 0, 0, -1, 1, 2, 3, -1, 2]
+richens	0.8	0.9798	[1, 0, 3, 0, 0, 0, 1, 2, 1, 0]
+richer	2.4	1.2	[1, 4, 2, 1, 2, 4, 4, 1, 3, 2]
+riches	2.4	1.0198	[2, 4, 1, 1, 2, 4, 3, 2, 3, 2]
+richest	2.4	1.11355	[4, 4, 2, 2, 3, 0, 2, 2, 3, 2]
+richly	1.9	0.53852	[2, 2, 2, 2, 3, 1, 2, 2, 1, 2]
+richness	2.2	0.74833	[2, 3, 2, 2, 2, 2, 2, 1, 4, 2]
+richnesses	2.1	0.9434	[2, 1, 2, 2, 3, 1, 3, 1, 4, 2]
+richweed	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
+richweeds	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
+ridicule	-2.0	0.63246	[-2, -2, -2, -2, -3, -2, -1, -2, -1, -3]
+ridiculed	-1.5	0.5	[-1, -1, -1, -2, -2, -2, -1, -2, -1, -2]
+ridiculer	-1.6	0.91652	[-1, -1, -1, -2, -2, 0, -1, -3, -2, -3]
+ridiculers	-1.6	0.66332	[-2, -1, -1, -2, -3, -2, -1, -2, -1, -1]
+ridicules	-1.8	0.6	[-1, -1, -2, -2, -2, -2, -1, -2, -2, -3]
+ridiculing	-1.8	0.6	[-2, -3, -2, -1, -1, -2, -2, -1, -2, -2]
+ridiculous	-1.5	0.67082	[-3, -2, -1, -1, -2, -1, -2, -1, -1, -1]
+ridiculously	-1.4	0.8	[-1, -2, -1, 0, -2, -1, -1, -3, -1, -2]
+ridiculousness	-1.1	1.51327	[-1, -1, -1, -2, -1, 3, -3, -2, -1, -2]
+ridiculousnesses	-1.6	1.11355	[-3, 0, -2, -2, -1, -1, -1, -4, -1, -1]
+rig	-0.5	1.0247	[0, 0, 0, 0, -2, 0, 0, 0, -3, 0]
+rigged	-1.5	1.0247	[-2, -3, -2, -1, -1, -2, 1, -1, -2, -2]
+rigid	-0.5	0.67082	[-2, -1, 0, 0, 0, 0, 0, -1, -1, 0]
+rigidification	-1.1	0.9434	[-1, -2, 0, 0, 0, -2, -2, -2, 0, -2]
+rigidifications	-0.8	0.9798	[-2, -1, 0, 0, -2, -1, 0, 1, -2, -1]
+rigidified	-0.7	1.00499	[0, -1, 0, 0, 0, 0, -2, 0, -1, -3]
+rigidifies	-0.6	0.8	[0, -1, 0, 0, 0, 0, -2, 0, -1, -2]
+rigidify	-0.3	0.64031	[0, 0, 0, 0, -1, 0, 0, 0, -2, 0]
+rigidities	-0.7	0.78102	[0, -1, 0, 0, 0, 0, -2, -1, -1, -2]
+rigidity	-0.7	0.64031	[-1, 0, -1, 0, -1, 0, -2, 0, -1, -1]
+rigidly	-0.7	0.45826	[-1, -1, -1, -1, 0, 0, -1, 0, -1, -1]
+rigidness	-0.3	1.00499	[0, -1, -1, 0, 2, -1, -1, -1, 1, -1]
+rigorous	-1.1	1.51327	[-2, -3, 1, 0, 1, 0, -1, -1, -3, -3]
+rigorously	-0.4	1.28062	[0, 2, 1, 0, -1, 0, -1, -1, -3, -1]
+riot	-2.6	1.0198	[-3, 0, -3, -2, -3, -3, -3, -4, -3, -2]
+riots	-2.3	0.78102	[-2, -3, -3, -2, -1, -1, -3, -2, -3, -3]
+risk	-1.1	0.7	[-1, -1, 0, -2, -1, 0, -2, -2, -1, -1]
+risked	-0.9	0.7	[-1, -2, 0, 0, -1, 0, -2, -1, -1, -1]
+risker	-0.8	0.4	[-1, -1, -1, 0, -1, 0, -1, -1, -1, -1]
+riskier	-1.4	0.91652	[0, -3, -1, 0, -1, -2, -1, -2, -2, -2]
+riskiest	-1.5	1.0247	[-2, -3, -1, -1, -3, 0, -1, -2, 0, -2]
+riskily	-0.7	1.34536	[-1, -2, -1, -1, 3, 0, -1, -1, -1, -2]
+riskiness	-1.3	1.00499	[-3, -1, -1, 0, -1, 0, -1, -3, -2, -1]
+riskinesses	-1.6	0.91652	[-2, -1, -1, 0, -3, -1, -2, -1, -3, -2]
+risking	-1.3	1.1	[0, 0, -2, 0, -1, -3, -3, -1, -2, -1]
+riskless	1.3	0.9	[2, 1, 0, 1, 1, 1, 2, 3, 0, 2]
+risks	-1.1	0.9434	[-1, 0, -1, -1, 0, 0, -2, -1, -3, -2]
+risky	-0.8	0.9798	[-1, 1, -1, -1, -1, 0, 0, -1, -3, -1]
+rob	-2.6	0.8	[-2, -4, -3, -2, -3, -4, -2, -2, -2, -2]
+robber	-2.6	1.0198	[-4, -1, -2, -3, -2, -1, -4, -3, -3, -3]
+robed	-0.7	0.9	[-2, 0, 0, 0, 0, -2, 0, -2, -1, 0]
+robing	-1.5	1.56525	[0, 0, 0, 0, -2, -3, -3, -4, -3, 0]
+robs	-2.0	1.0	[-2, -1, -3, -2, -2, -1, -4, -3, -1, -1]
+robust	1.4	1.42829	[1, 0, 0, 1, 4, 0, 2, 3, 3, 0]
+roflcopter	2.1	0.53852	[2, 2, 2, 1, 3, 2, 3, 2, 2, 2]
+romance	2.6	0.66332	[2, 3, 4, 2, 3, 2, 3, 2, 3, 2]
+romanced	2.2	0.87178	[2, 3, 2, 4, 2, 1, 2, 3, 1, 2]
+romancer	1.3	1.1	[0, 0, 2, 2, 2, 2, 3, 2, 0, 0]
+romancers	1.7	1.00499	[0, 2, 2, 2, 2, 2, 1, 3, 0, 3]
+romances	1.3	0.9	[0, 1, 2, 2, 2, 2, 2, 2, 0, 0]
+romancing	2.0	0.89443	[4, 1, 1, 2, 2, 2, 2, 1, 3, 2]
+romantic	1.7	0.78102	[2, 2, 2, 1, 2, 3, 2, 2, 0, 1]
+romantically	1.8	0.87178	[3, 1, 2, 0, 1, 2, 2, 2, 3, 2]
+romanticise	1.7	1.61555	[-1, 4, 2, 1, 3, 1, 3, 3, 2, -1]
+romanticised	1.7	0.9	[2, 2, 2, 2, 2, 2, 3, 0, 2, 0]
+romanticises	1.3	1.1	[2, 2, 1, 1, 1, 2, 3, -1, 2, 0]
+romanticising	2.7	0.78102	[3, 3, 3, 2, 1, 3, 2, 3, 4, 3]
+romanticism	2.2	1.32665	[1, 4, 2, 1, 3, 1, 3, 3, 4, 0]
+romanticisms	2.1	0.9434	[2, 3, 2, 1, 2, 3, 3, 2, 3, 0]
+romanticist	1.9	1.3	[1, 4, 2, 0, 3, 1, 2, 3, 3, 0]
+romanticists	1.3	1.00499	[2, 0, 0, 1, 3, 3, 1, 1, 1, 1]
+romanticization	1.5	1.36015	[1, 3, 2, 2, -1, 2, 0, 1, 4, 1]
+romanticizations	2.0	1.0	[4, 1, 3, 1, 2, 3, 1, 2, 2, 1]
+romanticize	1.8	0.9798	[2, 2, 1, 1, 2, 1, 3, 3, 3, 0]
+romanticized	0.9	1.22066	[0, 1, 1, 3, -1, 0, 1, 1, 3, 0]
+romanticizes	1.8	0.87178	[2, 3, 2, 1, 2, 3, 0, 1, 2, 2]
+romanticizing	1.2	1.07703	[0, 1, 2, 1, 3, 0, 1, 1, 0, 3]
+romantics	1.9	0.83066	[2, 3, 2, 1, 0, 2, 3, 2, 2, 2]
+rotten	-2.3	0.78102	[-2, -3, -1, -3, -3, -1, -3, -2, -3, -2]
+rude	-2.0	0.44721	[-2, -1, -3, -2, -2, -2, -2, -2, -2, -2]
+rudely	-2.2	0.87178	[-3, -2, -3, -1, -2, -4, -2, -2, -1, -2]
+rudeness	-1.5	0.67082	[-2, -1, -1, -1, -1, -3, -2, -2, -1, -1]
+ruder	-2.1	0.83066	[-2, -1, -4, -2, -3, -1, -2, -2, -2, -2]
+ruderal	-0.8	1.46969	[-3, 0, -1, -2, 0, -1, -3, 0, 2, 0]
+ruderals	-0.4	0.66332	[0, -1, 0, -2, 0, -1, 0, 0, 0, 0]
+rudesby	-2.0	0.7746	[-2, -3, -2, -2, -1, -3, -1, -1, -2, -3]
+rudest	-2.5	0.5	[-3, -2, -3, -3, -2, -2, -2, -3, -2, -3]
+ruin	-2.8	0.87178	[-3, -3, -1, -4, -4, -3, -3, -2, -2, -3]
+ruinable	-1.6	0.8	[-1, -2, -1, -3, -1, -3, -1, -1, -2, -1]
+ruinate	-2.8	0.87178	[-4, -4, -3, -3, -1, -3, -3, -3, -2, -2]
+ruinated	-1.5	1.56525	[0, -4, 0, -4, -1, -2, 0, -1, -3, 0]
+ruinates	-1.5	1.56525	[0, -4, 0, -4, -1, -2, 0, -1, -3, 0]
+ruinating	-1.5	1.20416	[-2, -2, -2, -3, 0, -1, 1, -3, -1, -2]
+ruination	-2.7	1.00499	[-4, -4, -3, -3, -2, -1, -3, -3, -3, -1]
+ruinations	-1.6	1.35647	[-2, -2, -3, -4, 0, -1, 1, -2, -1, -2]
+ruined	-2.1	0.7	[-3, -2, -2, -1, -2, -2, -3, -3, -1, -2]
+ruiner	-2.0	0.63246	[-1, -3, -2, -2, -1, -2, -3, -2, -2, -2]
+ruing	-1.6	0.91652	[-2, -1, -2, -1, -1, -1, -3, 0, -3, -2]
+ruining	-1.0	1.94936	[-3, -3, 0, -2, 1, -3, 2, -2, 2, -2]
+ruinous	-2.7	0.78102	[-2, -3, -3, -3, -3, -4, -2, -3, -1, -3]
+ruinously	-2.6	0.8	[-3, -2, -2, -3, -1, -3, -4, -2, -3, -3]
+ruinousness	-1.0	1.09545	[-1, -2, -3, -1, -1, -2, 1, 0, -1, 0]
+ruins	-1.9	0.9434	[-1, -2, -1, -2, -1, -2, -4, -1, -3, -2]
+sabotage	-2.4	0.91652	[-3, -3, -3, -2, -2, -4, -2, -3, -1, -1]
+sad	-2.1	0.9434	[-1, -1, -2, -2, -3, -2, -3, -2, -4, -1]
+sadden	-2.6	0.4899	[-2, -3, -2, -3, -2, -3, -2, -3, -3, -3]
+saddened	-2.4	0.4899	[-3, -2, -3, -2, -3, -3, -2, -2, -2, -2]
+saddening	-2.2	0.4	[-3, -2, -2, -2, -2, -2, -3, -2, -2, -2]
+saddens	-1.9	0.7	[-3, -1, -1, -1, -2, -2, -2, -2, -3, -2]
+sadder	-2.4	0.91652	[-2, -2, -3, -4, -3, -1, -3, -1, -2, -3]
+saddest	-3.0	0.63246	[-4, -3, -2, -3, -3, -2, -3, -4, -3, -3]
+sadly	-1.8	0.6	[-2, -2, -2, -1, -2, -3, -2, -1, -1, -2]
+sadness	-1.9	0.3	[-2, -1, -2, -2, -2, -2, -2, -2, -2, -2]
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+safecracker	-0.7	1.61555	[-3, -2, 0, -3, 0, -2, 0, 1, 2, 0]
+safecrackers	-0.9	1.04403	[-1, 0, -2, 0, -1, 0, 0, -3, 0, -2]
+safecracking	-0.9	0.9434	[0, 0, 0, 0, -2, 0, -1, -2, -2, -2]
+safecrackings	-0.7	1.67631	[-2, -1, -2, -4, 2, -1, -1, 0, 1, 1]
+safeguard	1.6	0.4899	[2, 2, 1, 1, 1, 2, 2, 2, 2, 1]
+safeguarded	1.5	0.92195	[1, 2, 2, 0, 2, 0, 3, 1, 2, 2]
+safeguarding	1.1	0.7	[2, 1, 1, 0, 1, 0, 2, 1, 1, 2]
+safeguards	1.4	0.66332	[1, 2, 1, 1, 0, 2, 2, 2, 2, 1]
+safekeeping	1.4	0.66332	[3, 1, 1, 2, 1, 1, 2, 1, 1, 1]
+safelight	1.1	1.22066	[0, 3, 0, 2, 0, 3, 0, 2, 1, 0]
+safelights	0.8	1.07703	[0, 3, 1, 0, 0, 2, 0, 2, 0, 0]
+safely	2.2	0.74833	[2, 2, 2, 3, 4, 2, 2, 1, 2, 2]
+safeness	1.5	0.67082	[1, 1, 1, 1, 3, 1, 2, 2, 2, 1]
+safer	1.8	0.6	[2, 1, 2, 3, 2, 2, 1, 1, 2, 2]
+safes	0.4	0.8	[0, 0, 2, 0, 0, 0, 0, 0, 2, 0]
+safest	1.7	1.61555	[2, 2, 2, 2, -3, 3, 3, 2, 2, 2]
+safeties	1.5	1.0247	[2, 0, 1, 3, 2, 1, 3, 1, 0, 2]
+safety	1.8	0.6	[2, 2, 2, 2, 1, 1, 2, 3, 1, 2]
+safetyman	0.3	0.64031	[0, 0, 0, 0, 2, 0, 1, 0, 0, 0]
+salient	1.1	1.22066	[1, 3, 0, -1, 0, 1, 2, 1, 1, 3]
+sappy	-1.0	1.18322	[-2, -1, 2, -2, -2, 0, -1, -1, -2, -1]
+sarcasm	-0.9	0.7	[0, -2, -1, -1, 0, 0, -1, -1, -2, -1]
+sarcasms	-0.9	0.7	[0, -1, 0, -1, -1, -2, 0, -1, -1, -2]
+sarcastic	-1.0	0.7746	[-1, -1, -1, -1, -1, -1, -1, -2, 1, -2]
+sarcastically	-1.1	1.37477	[-1, -4, 1, -1, -1, -2, 1, -2, -1, -1]
+satisfaction	1.9	0.9434	[1, 3, 2, 4, 2, 1, 1, 1, 2, 2]
+satisfactions	2.1	0.7	[3, 3, 3, 1, 2, 2, 1, 2, 2, 2]
+satisfactorily	1.6	1.11355	[1, 2, 2, -1, 2, 1, 3, 3, 1, 2]
+satisfactoriness	1.5	0.5	[1, 2, 1, 2, 2, 1, 2, 1, 2, 1]
+satisfactory	1.5	0.67082	[2, 3, 1, 1, 1, 2, 2, 1, 1, 1]
+satisfiable	1.9	0.83066	[3, 1, 2, 1, 2, 3, 1, 2, 3, 1]
+satisfied	1.8	0.6	[2, 2, 2, 1, 1, 2, 3, 1, 2, 2]
+satisfies	1.8	0.6	[3, 1, 2, 1, 1, 2, 2, 2, 2, 2]
+satisfy	2.0	0.63246	[3, 2, 2, 2, 2, 1, 1, 2, 3, 2]
+satisfying	2.0	1.48324	[2, 3, 2, 1, 3, 3, 3, 2, -2, 3]
+satisfyingly	1.9	0.9434	[1, 2, 2, 1, 2, 1, 4, 1, 3, 2]
+savage	-2.0	1.73205	[-3, -4, -3, 1, -2, -1, -3, -4, -2, 1]
+savaged	-2.0	1.34164	[-1, 0, -4, -3, -3, -3, -2, 0, -1, -3]
+savagely	-2.2	0.74833	[-2, -1, -3, -2, -2, -1, -2, -3, -3, -3]
+savageness	-2.6	1.0198	[-3, -1, -2, -3, -2, -1, -4, -4, -3, -3]
+savagenesses	-0.9	1.86815	[-2, 3, -1, -3, -2, 2, -3, -1, -1, -1]
+savageries	-1.9	1.75784	[-3, 1, -3, -4, -3, 1, -2, -3, 0, -3]
+savagery	-2.5	1.62788	[-2, -3, -3, -3, 2, -3, -3, -4, -4, -2]
+savages	-2.4	1.0198	[-2, -2, -3, -4, -3, -3, -2, 0, -2, -3]
+save	2.2	1.16619	[1, 3, 3, 1, 2, 1, 2, 4, 1, 4]
+saved	1.8	0.6	[1, 2, 2, 2, 1, 3, 2, 2, 1, 2]
+scam	-2.7	0.64031	[-2, -3, -3, -3, -2, -2, -4, -3, -3, -2]
+scams	-2.8	0.87178	[-3, -1, -3, -4, -4, -3, -2, -2, -3, -3]
+scandal	-1.9	1.81384	[-3, -2, -2, -4, 3, -3, -3, -1, -2, -2]
+scandalous	-2.4	0.8	[-2, -1, -3, -2, -4, -2, -3, -3, -2, -2]
+scandals	-2.2	0.9798	[-2, -3, -3, -2, -1, 0, -3, -3, -2, -3]
+scapegoat	-1.7	0.64031	[-3, -2, -2, -2, -1, -1, -1, -2, -1, -2]
+scapegoats	-1.4	0.8	[-1, -2, -2, -1, 0, -2, -2, 0, -2, -2]
+scare	-2.2	0.87178	[-2, -2, -4, -2, -3, -1, -2, -1, -2, -3]
+scarecrow	-0.8	0.9798	[-1, 0, -1, 0, 0, 0, -2, -3, -1, 0]
+scarecrows	-0.7	1.1	[2, 0, -1, -1, -1, -2, -1, -2, 0, -1]
+scared	-1.9	0.7	[-1, -1, -2, -3, -2, -3, -1, -2, -2, -2]
+scaremonger	-2.1	0.53852	[-1, -2, -2, -3, -2, -2, -3, -2, -2, -2]
+scaremongers	-2.0	1.0	[-2, -2, 0, -4, -2, -2, -1, -2, -3, -2]
+scarer	-1.7	0.78102	[-2, -1, -1, -2, -3, -1, -3, -1, -2, -1]
+scarers	-1.3	0.9	[-1, -2, -1, 0, 0, -1, -3, -2, -1, -2]
+scares	-1.4	0.4899	[-1, -1, -2, -1, -1, -2, -1, -2, -2, -1]
+scarey	-1.7	0.64031	[-1, -1, -2, -2, -1, -2, -1, -2, -3, -2]
+scaring	-1.9	1.22066	[-3, -2, -1, -3, -1, -3, -2, -2, 1, -3]
+scary	-2.2	0.87178	[-2, -1, -4, -3, -3, -2, -2, -2, -2, -1]
+sceptic	-1.0	0.89443	[-3, 0, -1, -1, -1, 0, 0, -2, -1, -1]
+sceptical	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+scepticism	-0.8	0.87178	[-1, -2, -2, 0, 0, -1, 1, -1, -1, -1]
+sceptics	-0.7	0.78102	[0, 0, 0, -1, -2, 0, -1, -1, 0, -2]
+scold	-1.7	0.78102	[-2, -1, -1, -1, -3, -3, -2, -2, -1, -1]
+scoop	0.6	0.8	[0, 0, 1, 0, 2, 0, 2, 0, 1, 0]
+scorn	-1.7	0.64031	[-2, -3, -2, -1, -1, -1, -1, -2, -2, -2]
+scornful	-1.8	1.16619	[-3, -3, -2, -1, -4, 0, -2, -1, -1, -1]
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+sins	-2.0	1.0	[-2, -1, -2, -3, -1, -4, -3, -2, -1, -1]
+skeptic	-0.9	1.13578	[0, 0, -1, -1, -1, 0, -2, -2, 1, -3]
+skeptical	-1.3	0.9	[0, -3, -2, -2, -1, -2, 0, -1, -1, -1]
+skeptically	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -2]
+skepticism	-1.0	0.89443	[0, 0, -1, -1, -1, -1, 0, -1, -3, -2]
+skepticisms	-1.2	0.9798	[1, -2, 0, -1, -2, -1, -2, -2, -1, -2]
+skeptics	-0.4	0.91652	[-2, 0, 0, -1, -1, 1, -1, 0, 1, -1]
+slam	-1.6	1.11355	[-2, -1, -3, -1, -3, -2, -1, -2, 1, -2]
+slash	-1.1	1.22066	[-2, -3, -2, 0, -2, 0, -1, -2, 0, 1]
+slashed	-0.9	0.83066	[-2, -1, -2, -1, -1, 0, 1, -1, -1, -1]
+slashes	-0.8	0.6	[0, -1, -2, -1, 0, 0, -1, -1, -1, -1]
+slashing	-1.1	1.86815	[-3, -2, -3, -3, 3, 1, 0, -1, -2, -1]
+slavery	-3.8	0.4	[-4, -3, -4, -3, -4, -4, -4, -4, -4, -4]
+sleeplessness	-1.6	1.49666	[-3, -4, -2, -1, -2, -2, -2, 2, -1, -1]
+slicker	0.4	1.28062	[-2, 1, -1, 2, 0, 0, 2, 2, 0, 0]
+slickest	0.3	1.00499	[1, 0, -1, 0, -1, 0, 0, 0, 2, 2]
+sluggish	-1.7	0.64031	[-1, -2, -1, -3, -2, -2, -1, -2, -1, -2]
+slut	-2.8	0.87178	[-4, -2, -2, -1, -3, -3, -3, -3, -4, -3]
+sluts	-2.7	1.48661	[-3, -3, -4, -4, -3, -4, -1, -3, 1, -3]
+sluttier	-2.7	1.18743	[-2, -2, -4, -3, -4, -4, -1, -1, -2, -4]
+sluttiest	-3.1	0.83066	[-3, -4, -3, -4, -3, -4, -2, -2, -4, -2]
+sluttish	-2.2	0.87178	[-2, -3, -3, -2, -2, -4, -2, -1, -1, -2]
+sluttishly	-2.1	1.13578	[-2, 0, -2, -3, -1, -2, -3, -1, -3, -4]
+sluttishness	-2.5	0.92195	[-2, -1, -3, -4, -2, -1, -3, -3, -3, -3]
+sluttishnesses	-2.0	1.09545	[0, -2, -1, -3, -3, -1, -3, -1, -3, -3]
+slutty	-2.3	0.9	[-3, -1, -3, -3, -3, -2, -1, -3, -1, -3]
+smart	1.7	0.78102	[2, 2, 1, 2, 1, 3, 2, 0, 2, 2]
+smartass	-2.1	0.83066	[-1, -1, -2, -3, -2, -1, -2, -3, -3, -3]
+smartasses	-1.7	2.05183	[-1, -2, -3, -3, -3, -1, -2, -3, 4, -3]
+smarted	0.7	1.41774	[2, 1, -2, 1, 1, 2, 2, 2, -1, -1]
+smarten	1.9	0.7	[3, 1, 2, 1, 2, 2, 2, 3, 1, 2]
+smartened	1.5	0.67082	[2, 2, 1, 3, 1, 1, 1, 1, 2, 1]
+smartening	1.7	0.9	[1, 3, 3, 1, 1, 1, 2, 1, 1, 3]
+smartens	1.5	0.5	[2, 2, 1, 1, 1, 1, 2, 2, 2, 1]
+smarter	2.0	0.7746	[2, 2, 1, 1, 2, 2, 2, 2, 4, 2]
+smartest	3.0	1.0	[4, 3, 4, 3, 2, 2, 4, 3, 1, 4]
+smartie	1.3	0.9	[1, 4, 1, 1, 1, 1, 1, 1, 1, 1]
+smarties	1.7	0.9	[1, 1, 2, 4, 2, 2, 1, 2, 1, 1]
+smarting	-0.7	1.9	[2, 3, -1, -2, 1, -2, -1, -3, -2, -2]
+smartly	1.5	0.67082	[2, 1, 1, 1, 1, 2, 1, 3, 1, 2]
+smartness	2.0	0.89443	[1, 3, 3, 1, 2, 1, 2, 3, 1, 3]
+smartnesses	1.5	0.92195	[1, 0, 1, 1, 1, 2, 1, 2, 3, 3]
+smarts	1.6	0.66332	[2, 1, 3, 1, 2, 1, 2, 1, 2, 1]
+smartweed	0.2	0.6	[0, 0, 0, 0, 0, 2, 0, 0, 0, 0]
+smartweeds	0.1	0.53852	[0, 0, -1, 0, 0, 0, 1, 0, 0, 1]
+smarty	1.1	0.53852	[0, 2, 1, 2, 1, 1, 1, 1, 1, 1]
+smear	-1.5	1.20416	[-2, -1, -1, -2, -3, 0, 0, -4, -1, -1]
+smilax	0.6	0.66332	[0, 2, 1, 0, 0, 0, 1, 1, 1, 0]
+smilaxes	0.3	0.78102	[0, 0, 0, 0, 1, 2, 1, -1, 0, 0]
+smile	1.5	0.67082	[2, 1, 1, 1, 2, 2, 3, 1, 1, 1]
+smiled	2.5	0.80623	[3, 2, 3, 2, 1, 2, 3, 4, 3, 2]
+smileless	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -1, -2, -2]
+smiler	1.7	0.78102	[1, 1, 3, 1, 3, 2, 2, 2, 1, 1]
+smiles	2.1	1.04403	[2, 4, 2, 1, 3, 1, 1, 3, 1, 3]
+smiley	1.7	0.78102	[1, 2, 1, 2, 2, 0, 2, 3, 2, 2]
+smileys	1.5	0.92195	[1, 2, 1, 3, 1, 0, 1, 3, 1, 2]
+smiling	2.0	1.18322	[2, 1, 1, 1, 2, 3, 4, 1, 4, 1]
+smilingly	2.3	0.64031	[3, 2, 3, 2, 3, 1, 2, 2, 2, 3]
+smog	-1.2	0.6	[-1, -1, -2, -1, -1, -2, -2, -1, 0, -1]
+smother	-1.8	0.87178	[-2, -2, -3, -1, -2, -1, -2, -2, -3, 0]
+smothered	-0.9	1.7	[2, -4, 0, -1, -3, -2, 0, -1, 1, -1]
+smothering	-1.4	1.56205	[-2, -3, -1, -4, 0, -2, -1, 2, -1, -2]
+smothers	-1.9	1.04403	[-1, -1, -3, -1, -2, -3, 0, -2, -3, -3]
+smothery	-1.1	0.7	[-2, 0, -2, -1, -2, -1, 0, -1, -1, -1]
+smug	0.8	1.16619	[-1, 2, 0, 2, 1, -1, 2, 1, 0, 2]
+smugger	-1.0	0.89443	[1, -2, -1, -2, -1, -1, -1, 0, -2, -1]
+smuggest	-1.5	1.28452	[-1, -1, -1, 1, -1, -3, -4, -2, -1, -2]
+smuggle	-1.6	1.11355	[-2, -1, -1, -1, -2, 0, -1, -1, -3, -4]
+smuggled	-1.5	0.92195	[-1, -1, -2, -1, -1, -1, -2, -1, -1, -4]
+smuggler	-2.1	1.22066	[-1, -3, -3, -1, -1, -1, -4, -1, -2, -4]
+smugglers	-1.4	1.56205	[-2, -3, -4, 1, -2, 0, -2, 1, -1, -2]
+smuggles	-1.7	1.00499	[-1, -2, -2, -1, -1, -1, -3, -1, -1, -4]
+smuggling	-2.1	0.83066	[-3, -2, -2, -1, -2, -2, -1, -2, -4, -2]
+smugly	0.2	1.249	[-1, 2, -1, -1, 1, 1, -1, 1, 2, -1]
+smugness	-1.4	1.11355	[-1, -1, -1, -3, -3, -2, 1, -1, -2, -1]
+smugnesses	-1.7	0.78102	[-1, -1, -2, -1, -3, -1, -2, -2, -3, -1]
+sneaky	-0.9	0.7	[-1, -1, -1, -2, -1, -1, -1, 1, -1, -1]
+snob	-2.0	0.63246	[-2, -2, -2, -2, -2, -1, -3, -1, -3, -2]
+snobbery	-2.0	0.63246	[-1, -2, -2, -2, -2, -3, -2, -1, -3, -2]
+snobbier	-0.7	1.00499	[-1, 2, -1, -1, -1, -1, -1, 0, -2, -1]
+snobbiest	-0.5	1.11803	[-2, -2, 1, -1, 1, -1, 0, -1, 1, -1]
+snobbily	-1.6	1.11355	[-1, -2, -2, -2, -1, -3, -3, -1, 1, -2]
+snobbish	-0.9	1.37477	[-2, -1, 1, -1, 1, -2, -3, -2, 1, -1]
+snobbishly	-1.2	1.249	[-2, 1, -2, -1, -2, -3, -1, -2, -1, 1]
+snobbishness	-1.1	1.22066	[-1, -2, -2, -1, -3, -1, -1, -1, 2, -1]
+snobbishnesses	-1.7	0.78102	[-2, -1, -3, -2, -1, -1, -2, -1, -3, -1]
+snobbism	-1.0	1.41421	[-2, -1, 1, -1, 1, -2, -3, -2, 1, -2]
+snobbisms	-0.3	1.18743	[1, -1, -1, 0, -1, -1, 1, -2, 2, -1]
+snobby	-1.7	1.00499	[-1, -1, -1, -3, -2, -2, 0, -3, -3, -1]
+snobs	-1.4	1.0198	[-2, -1, -1, -2, -2, -3, -1, -2, 1, -1]
+snub	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -2, -1, -2]
+snubbed	-2.0	0.7746	[-2, -2, 0, -2, -3, -2, -2, -2, -3, -2]
+snubbing	-0.9	1.13578	[-2, -1, -1, -1, 1, -1, -3, 1, -1, -1]
+snubs	-2.1	0.9434	[-2, -1, -1, -1, -3, -2, -4, -3, -2, -2]
+sob	-1.0	1.34164	[-1, -2, -2, -2, -1, -1, 2, 1, -2, -2]
+sobbed	-1.9	1.3	[-2, -4, 1, -1, -3, -1, -3, -2, -2, -2]
+sobbing	-1.6	1.49666	[1, -2, -3, -1, -1, -3, 1, -2, -3, -3]
+sobering	-0.8	1.32665	[2, -2, 0, -2, -1, -1, -2, 1, -1, -2]
+sobs	-2.5	0.67082	[-3, -3, -2, -2, -3, -3, -3, -1, -2, -3]
+sociabilities	1.2	0.9798	[1, 3, 1, 2, 0, 1, 0, 2, 2, 0]
+sociability	1.1	0.9434	[0, 1, 1, 1, 0, 2, 1, 0, 2, 3]
+sociable	1.9	0.7	[1, 1, 2, 3, 1, 2, 2, 2, 3, 2]
+sociableness	1.5	0.5	[1, 1, 1, 2, 2, 2, 1, 2, 1, 2]
+sociably	1.6	0.91652	[3, 2, 0, 1, 3, 2, 1, 1, 2, 1]
+sok	1.3	1.1	[0, 1, 2, 1, 1, 0, 1, 4, 2, 1]
+solemn	-0.3	1.1	[-1, -2, -1, 0, -1, 2, 0, -1, 1, 0]
+solemnified	-0.5	0.67082	[0, 0, 0, 0, -1, -1, -1, 0, -2, 0]
+solemnifies	-0.5	0.67082	[0, 0, 0, 0, -1, -2, -1, 0, -1, 0]
+solemnify	0.3	1.18743	[2, 1, 2, 1, 0, 0, -2, -1, 0, 0]
+solemnifying	0.1	1.3	[2, -1, 0, -3, 0, 1, 1, 1, 0, 0]
+solemnities	0.3	0.78102	[0, 1, -1, 0, 0, 0, 2, 1, 0, 0]
+solemnity	-1.1	0.9434	[0, -2, 0, -2, -2, -1, -2, 0, 0, -2]
+solemnization	0.7	1.34536	[-1, -1, 0, 2, 2, 0, 3, 2, 0, 0]
+solemnize	0.3	0.78102	[1, -1, 0, 2, 0, 0, 1, 0, 0, 0]
+solemnized	-0.7	0.9	[0, 0, 0, -1, -1, -1, -1, 0, 0, -3]
+solemnizes	0.6	0.91652	[0, 0, 0, 0, 0, 0, 2, 2, 2, 0]
+solemnizing	-0.6	0.8	[0, 0, -1, -1, 0, 0, -2, -2, 0, 0]
+solemnly	0.8	0.9798	[0, 2, 0, 1, 1, 2, -1, 2, 1, 0]
+solid	0.6	0.8	[0, 2, 1, 2, 0, 1, 0, 0, 0, 0]
+solidarity	1.2	0.6	[1, 1, 1, 1, 2, 0, 1, 2, 2, 1]
+solution	1.3	0.64031	[1, 2, 1, 2, 1, 1, 2, 2, 0, 1]
+solutions	0.7	0.78102	[1, 1, 2, 0, 1, 0, 2, 0, 0, 0]
+solve	0.8	0.4	[0, 1, 1, 1, 1, 0, 1, 1, 1, 1]
+solved	1.1	0.53852	[1, 2, 1, 0, 1, 1, 1, 2, 1, 1]
+solves	1.1	0.7	[2, 0, 1, 0, 1, 2, 1, 2, 1, 1]
+solving	1.4	0.8	[0, 3, 1, 2, 1, 1, 2, 1, 2, 1]
+somber	-1.8	0.6	[-1, -2, -2, -3, -2, -1, -2, -1, -2, -2]
+son-of-a-bitch	-2.7	0.64031	[-3, -3, -3, -1, -2, -3, -3, -3, -3, -3]
+soothe	1.5	0.92195	[3, 2, 2, 1, 2, 0, 2, 0, 2, 1]
+soothed	0.5	1.43178	[2, -3, 1, 1, 0, 1, 1, 1, 2, -1]
+soothing	1.3	0.64031	[2, 1, 2, 1, 1, 1, 2, 0, 2, 1]
+sophisticated	2.6	0.91652	[3, 4, 3, 3, 3, 1, 2, 1, 3, 3]
+sore	-1.5	0.5	[-2, -2, -2, -1, -1, -1, -2, -1, -1, -2]
+sorrow	-2.4	0.8	[-2, -2, -2, -1, -2, -3, -2, -4, -3, -3]
+sorrowed	-2.4	0.8	[-1, -2, -3, -3, -2, -3, -2, -4, -2, -2]
+sorrower	-2.3	0.78102	[-1, -2, -1, -3, -3, -2, -2, -3, -3, -3]
+sorrowful	-2.2	0.6	[-3, -3, -2, -2, -2, -2, -3, -1, -2, -2]
+sorrowfully	-2.3	0.64031	[-3, -3, -2, -1, -2, -2, -3, -2, -2, -3]
+sorrowfulness	-2.5	0.67082	[-4, -3, -2, -3, -2, -3, -2, -2, -2, -2]
+sorrowing	-1.7	1.26886	[-2, -2, 1, -1, -1, -2, -4, -3, -2, -1]
+sorrows	-1.6	0.66332	[-1, -1, -2, -1, -2, -2, -1, -2, -1, -3]
+sorry	-0.3	1.61555	[-1, 0, -1, -2, -1, -1, 4, 1, -1, -1]
+soulmate	2.9	0.83066	[4, 2, 2, 2, 3, 4, 3, 3, 2, 4]
+spam	-1.5	1.0247	[-1, -1, -1, -2, 1, -2, -3, -2, -2, -2]
+spammer	-2.2	0.6	[-3, -2, -2, -1, -2, -3, -2, -2, -3, -2]
+spammers	-1.6	1.11355	[-2, -1, -2, -3, -2, -1, -2, -1, 1, -3]
+spamming	-2.1	0.83066	[-3, -3, -1, -3, -2, -1, -2, -2, -1, -3]
+spark	0.9	1.04403	[0, 2, 1, 1, 0, 1, 3, -1, 1, 1]
+sparkle	1.8	0.74833	[0, 2, 2, 2, 1, 2, 3, 2, 2, 2]
+sparkles	1.3	1.18743	[3, 2, 0, 0, 3, 0, 2, 0, 1, 2]
+sparkling	1.2	0.4	[1, 1, 1, 2, 1, 1, 1, 2, 1, 1]
+special	1.7	0.78102	[3, 1, 3, 2, 2, 1, 1, 2, 1, 1]
+speculative	0.4	1.11355	[1, -1, 1, 0, -1, -1, 1, 2, 2, 0]
+spirit	0.7	1.00499	[0, 0, 1, 2, 3, 1, 0, 0, 0, 0]
+spirited	1.3	1.00499	[1, 1, 0, 1, 1, 3, 2, 3, 0, 1]
+spiritless	-1.3	0.64031	[-2, -1, -1, -2, -2, -1, 0, -1, -2, -1]
+spite	-2.4	0.8	[-2, -2, -3, -2, -3, -2, -4, -1, -3, -2]
+spited	-2.4	0.91652	[-2, -3, -3, -4, -2, -1, -2, -1, -3, -3]
+spiteful	-1.9	1.75784	[-2, 3, -2, -3, -2, -3, -2, -2, -4, -2]
+spitefully	-2.3	0.78102	[-2, -2, -1, -3, -3, -2, -2, -2, -4, -2]
+spitefulness	-1.5	1.74642	[-3, -2, 1, -3, -3, -3, -2, 2, 0, -2]
+spitefulnesses	-2.3	0.9	[-1, -4, -2, -3, -3, -2, -2, -3, -1, -2]
+spites	-1.4	1.28062	[0, -2, -2, -3, -2, -1, 1, 0, -3, -2]
+splendent	2.7	0.78102	[3, 2, 1, 3, 2, 3, 4, 3, 3, 3]
+splendid	2.8	0.9798	[4, 2, 3, 4, 2, 2, 3, 1, 3, 4]
+splendidly	2.1	1.22066	[1, 4, 1, 3, 3, 4, 1, 2, 1, 1]
+splendidness	2.3	0.9	[2, 1, 3, 3, 4, 2, 1, 3, 2, 2]
+splendiferous	2.6	1.95959	[4, 4, 3, -3, 3, 3, 4, 2, 3, 3]
+splendiferously	1.9	1.3	[2, 4, 4, 3, 0, 1, 1, 1, 2, 1]
+splendiferousness	1.7	1.18743	[1, 2, 3, 1, 2, 3, 3, 2, -1, 1]
+splendor	3.0	0.63246	[3, 3, 3, 3, 3, 2, 4, 4, 3, 2]
+splendorous	2.2	0.87178	[4, 2, 1, 2, 2, 3, 3, 1, 2, 2]
+splendors	2.0	0.44721	[2, 2, 2, 2, 3, 2, 2, 2, 1, 2]
+splendour	2.2	0.6	[2, 2, 2, 3, 3, 1, 2, 3, 2, 2]
+splendours	2.2	1.249	[3, 0, 2, 1, 4, 3, 2, 4, 1, 2]
+splendrous	2.2	1.16619	[4, 4, 3, 2, 1, 1, 3, 1, 2, 1]
+sprightly	2.0	0.89443	[0, 2, 3, 2, 2, 1, 2, 3, 3, 2]
+squelched	-1.0	0.63246	[-1, -1, -1, -1, 0, -2, -1, 0, -1, -2]
+stab	-2.8	0.6	[-3, -2, -2, -3, -3, -3, -3, -2, -4, -3]
+stabbed	-1.9	1.22066	[-2, -1, -3, -2, -2, 1, -3, -3, -1, -3]
+stable	1.2	0.74833	[1, 2, 2, 0, 1, 2, 1, 1, 2, 0]
+stabs	-1.9	1.13578	[-3, -3, -4, 0, -1, -2, -2, -2, -1, -1]
+stall	-0.8	0.74833	[-1, 0, -1, 0, -1, 0, -2, 0, -2, -1]
+stalled	-0.8	0.87178	[-2, -1, 0, -1, -1, 0, 1, -2, -1, -1]
+stalling	-0.8	1.4	[-3, -2, -1, -1, 0, 2, 1, -2, -1, -1]
+stamina	1.2	0.9798	[1, 0, 3, 0, 1, 2, 2, 1, 2, 0]
+stammer	-0.9	0.3	[-1, 0, -1, -1, -1, -1, -1, -1, -1, -1]
+stammered	-0.9	0.7	[-2, -1, -1, -1, 1, -1, -1, -1, -1, -1]
+stammerer	-1.1	0.3	[-1, -2, -1, -1, -1, -1, -1, -1, -1, -1]
+stammerers	-0.8	0.4	[-1, -1, -1, -1, -1, 0, 0, -1, -1, -1]
+stammering	-1.0	0.63246	[-2, -1, 0, -1, -1, -2, 0, -1, -1, -1]
+stammers	-0.8	0.4	[-1, -1, -1, 0, -1, -1, -1, 0, -1, -1]
+stampede	-1.8	1.07703	[-2, -3, -2, -3, 0, 0, -2, -1, -2, -3]
+stank	-1.9	1.04403	[-2, -2, -2, -1, -2, -4, -3, 0, -1, -2]
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+sunny	1.8	0.87178	[2, 2, 1, 2, 0, 2, 3, 3, 2, 1]
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+super	2.9	0.7	[4, 2, 4, 3, 3, 3, 2, 3, 2, 3]
+superb	3.1	0.9434	[3, 4, 2, 4, 3, 1, 3, 3, 4, 4]
+superior	2.5	1.11803	[2, 3, 1, 3, 3, 0, 3, 3, 4, 3]
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+supporting	1.9	0.9434	[3, 2, 1, 1, 3, 3, 1, 1, 3, 1]
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+supremacies	0.8	1.72047	[3, -2, 3, 0, 0, 2, -1, 3, 0, 0]
+supremacist	0.5	2.15639	[3, 2, -3, 1, 2, 2, 2, -2, 1, -3]
+supremacists	-1.0	1.89737	[-4, -2, -1, -3, -2, 2, 2, 0, 0, -2]
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+suprematists	0.4	1.56205	[2, 1, 0, 0, 2, 2, 2, -2, -1, -2]
+supreme	2.6	1.11355	[2, 3, 2, 1, 4, 2, 1, 3, 4, 4]
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+supremer	2.3	1.1	[4, 3, 3, 0, 1, 2, 3, 2, 3, 2]
+supremest	2.2	1.98997	[4, 3, 1, 0, 4, 4, -2, 3, 1, 4]
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+supremos	1.3	0.78102	[0, 2, 2, 1, 0, 2, 2, 1, 2, 1]
+sure	1.3	0.64031	[1, 1, 3, 1, 1, 2, 1, 1, 1, 1]
+surefire	1.0	0.7746	[1, 1, 0, 2, 2, 1, 0, 1, 2, 0]
+surefooted	1.9	0.83066	[0, 3, 2, 2, 2, 2, 1, 2, 3, 2]
+surefootedly	1.6	0.91652	[1, 1, 2, 0, 2, 1, 3, 3, 1, 2]
+surefootedness	1.5	1.20416	[2, 1, 4, 1, 0, 3, 2, 1, 1, 0]
+surely	1.9	0.7	[2, 2, 2, 1, 1, 1, 3, 2, 3, 2]
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+surest	1.3	0.78102	[2, 0, 2, 2, 2, 1, 0, 1, 1, 2]
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+surety	1.0	0.44721	[1, 1, 1, 1, 1, 0, 1, 1, 2, 1]
+suretyship	-0.1	1.51327	[-1, 0, 0, -2, -1, 2, -2, 3, 0, 0]
+suretyships	0.4	0.66332	[0, 0, 0, 1, 0, 0, 1, 0, 0, 2]
+surprisal	1.5	0.80623	[3, 1, 1, 2, 1, 2, 2, 1, 2, 0]
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+surprised	0.9	0.9434	[2, 0, 0, 0, 0, 2, 2, 1, 2, 0]
+surpriser	0.6	0.66332	[2, 0, 0, 0, 0, 1, 1, 1, 1, 0]
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+surprising	1.1	0.9434	[1, 1, 1, 0, 0, 2, 0, 1, 3, 2]
+surprisingly	1.2	0.87178	[1, 0, 2, 0, 0, 2, 2, 1, 2, 2]
+survived	2.3	0.78102	[3, 4, 2, 2, 2, 1, 2, 3, 2, 2]
+surviving	1.2	0.87178	[1, 3, 1, 0, 2, 0, 1, 1, 1, 2]
+survivor	1.5	1.0247	[1, 3, 2, 3, 1, 0, 0, 1, 2, 2]
+suspect	-1.2	0.9798	[0, -1, -1, -2, -2, -2, 1, -1, -2, -2]
+suspected	-0.9	1.13578	[-1, 0, -1, -2, -1, -1, -2, 2, -2, -1]
+suspecting	-0.7	1.34536	[-1, 2, -1, -1, -1, 1, -2, -1, -3, 0]
+suspects	-1.4	0.91652	[-2, -2, -2, -1, -2, -1, -2, -2, 1, -1]
+suspend	-1.3	0.64031	[0, -2, -1, -2, -1, -1, -2, -1, -2, -1]
+suspended	-2.1	0.83066	[-2, -1, -2, -3, -3, -1, -3, -1, -2, -3]
+suspicion	-1.6	0.91652	[-2, -2, -1, -2, 1, -2, -2, -2, -2, -2]
+suspicions	-1.5	0.67082	[-1, -2, -1, -2, -1, -1, -3, -1, -2, -1]
+suspicious	-1.5	0.67082	[-1, -2, -1, -1, -2, -1, -2, -1, -3, -1]
+suspiciously	-1.7	0.45826	[-2, -2, -1, -2, -1, -2, -2, -1, -2, -2]
+suspiciousness	-1.2	1.46969	[-2, -3, -2, -1, -1, 1, 2, -2, -2, -2]
+sux	-1.5	0.92195	[-1, -1, -2, -1, -2, -1, -3, 0, -3, -1]
+swear	-0.2	1.53623	[-2, 2, -1, 1, 1, 0, -1, -2, 2, -2]
+swearing	-1.0	1.09545	[0, -2, -1, -1, -2, 0, 1, -3, -1, -1]
+swears	0.2	1.4	[1, -2, 2, 0, 1, -2, -1, 2, 1, 0]
+sweet	2.0	0.63246	[1, 2, 2, 2, 3, 3, 2, 1, 2, 2]
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+sweetie	2.2	0.6	[2, 3, 3, 2, 1, 3, 2, 2, 2, 2]
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+sweetness	2.2	0.74833	[3, 2, 3, 1, 2, 2, 3, 3, 2, 1]
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+swiftly	1.2	0.9798	[0, 3, 1, 0, 1, 1, 1, 3, 1, 1]
+swindle	-2.4	1.0198	[-1, -4, -1, -3, -3, -2, -2, -2, -4, -2]
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+swindling	-2.0	1.0	[-2, -2, -2, -4, -1, 0, -3, -2, -2, -2]
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+sympathy	1.5	1.11803	[-1, 2, 3, 2, 1, 1, 1, 2, 1, 3]
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+talentless	-1.6	0.4899	[-2, -2, -2, -1, -2, -1, -1, -1, -2, -2]
+talents	2.0	1.18322	[2, 4, 1, 2, 0, 2, 4, 2, 2, 1]
+tantrum	-1.8	1.16619	[-3, -2, -2, -3, -1, 0, -1, 0, -3, -3]
+tantrums	-1.5	1.36015	[-1, -2, -4, -2, -2, -1, -1, 0, 1, -3]
+tard	-2.5	0.92195	[-3, -3, -3, -2, -2, -3, -1, -4, -1, -3]
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+teased	-1.2	0.87178	[0, -2, -2, -1, -1, -1, 0, -3, -1, -1]
+teasel	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
+teaseled	-0.8	0.74833	[-1, 0, -1, 0, 0, -1, -2, -1, -2, 0]
+teaseler	-0.8	0.87178	[0, 0, -2, 0, 0, -1, -2, -1, -2, 0]
+teaselers	-1.2	1.249	[0, -3, 0, 0, 0, -3, -2, -2, -2, 0]
+teaseling	-0.4	0.91652	[-1, 0, -3, 0, 0, 0, 0, 0, 0, 0]
+teaselled	-0.4	0.91652	[0, -3, 0, 0, 0, 0, -1, 0, 0, 0]
+teaselling	-0.2	0.4	[0, 0, 0, 0, -1, 0, -1, 0, 0, 0]
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+teaser	-1.0	1.18322	[0, -1, -3, -1, -1, -1, 0, -3, -1, 1]
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+teases	-1.2	0.74833	[-1, -1, 0, -1, -2, -1, -3, -1, -1, -1]
+teashops	0.2	0.4	[0, 1, 0, 1, 0, 0, 0, 0, 0, 0]
+teasing	-0.3	1.1	[0, 0, 1, 1, -1, 0, 0, 0, -1, -3]
+teasingly	-0.4	1.11355	[0, 1, 1, 0, -2, 0, -2, 0, -2, 0]
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+teaspoons	0.5	0.80623	[0, 0, 0, 2, 0, 0, 1, 2, 0, 0]
+teaspoonsful	0.3	0.9	[2, 0, 0, 0, 0, 2, 0, -1, 0, 0]
+temper	-1.8	0.4	[-1, -2, -2, -2, -2, -2, -2, -2, -1, -2]
+tempers	-1.3	0.64031	[-1, -1, 0, -1, -1, -2, -2, -2, -1, -2]
+tendered	0.5	0.92195	[0, 0, 2, 1, -1, -1, 1, 1, 1, 1]
+tenderer	0.6	0.66332	[0, 1, 1, 0, 0, 0, 2, 1, 1, 0]
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+tenderfoot	-0.1	0.53852	[-1, 1, 0, 0, 0, 0, 0, -1, 0, 0]
+tenderfoots	-0.5	1.11803	[1, -1, 0, 0, 0, -1, -1, 1, -3, -1]
+tenderhearted	1.5	1.0247	[2, 2, 1, 2, 3, 1, 1, -1, 2, 2]
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+tendering	0.6	0.66332	[0, 0, 1, 1, 1, 0, 0, 1, 2, 0]
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+tensed	-1.0	0.44721	[-1, 0, -1, -1, -1, -1, -2, -1, -1, -1]
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+tensing	-1.0	0.44721	[-1, -2, -1, 0, -1, -1, -1, -1, -1, -1]
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+tensional	-0.8	0.74833	[-1, 0, -1, -1, -1, -2, 1, -1, -1, -1]
+tensioned	-0.4	1.11355	[-2, 0, -1, 2, -1, 0, -1, -1, -1, 1]
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+tensioners	-0.9	1.04403	[-1, 0, -2, -2, -1, 1, -2, 0, 0, -2]
+tensioning	-1.4	1.0198	[-1, -1, -1, -1, 0, -2, -3, -3, 0, -2]
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+tensions	-1.7	0.78102	[-1, -3, -1, -1, -2, -2, -3, -1, -2, -1]
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+terrified	-3.0	0.63246	[-2, -3, -3, -3, -4, -3, -4, -2, -3, -3]
+terrifies	-2.6	1.0198	[-2, -4, -3, -3, -4, -1, -2, -3, -1, -3]
+terrify	-2.3	0.78102	[-3, -3, -2, -2, -1, -4, -2, -2, -2, -2]
+terrifying	-2.7	0.78102	[-4, -3, -3, -2, -2, -2, -4, -2, -3, -2]
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+terrorise	-3.1	0.83066	[-2, -3, -4, -4, -3, -3, -2, -4, -2, -4]
+terrorised	-3.3	0.64031	[-3, -3, -4, -3, -2, -4, -4, -3, -4, -3]
+terrorises	-3.3	0.45826	[-3, -3, -4, -3, -3, -4, -4, -3, -3, -3]
+terrorising	-3.0	0.44721	[-3, -3, -3, -3, -2, -3, -4, -3, -3, -3]
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+terroristic	-3.3	0.78102	[-4, -3, -2, -3, -4, -3, -4, -2, -4, -4]
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+terrorizes	-3.1	0.53852	[-2, -3, -3, -4, -3, -4, -3, -3, -3, -3]
+terrorizing	-3.0	1.0	[-3, -1, -4, -4, -4, -3, -2, -3, -2, -4]
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+thanks	1.9	1.04403	[1, 1, 1, 1, 3, 2, 1, 4, 3, 2]
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+threatener	-1.4	1.68523	[-2, -2, -3, -2, 3, 0, -2, -3, -1, -2]
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+triumphing	2.3	0.64031	[2, 2, 3, 2, 2, 3, 2, 3, 1, 3]
+triumphs	2.0	1.41421	[3, 2, 3, 3, 3, 1, -1, 1, 1, 4]
+trivial	-0.1	0.83066	[0, -1, -1, 0, 1, 0, 1, -1, 1, -1]
+trivialise	-0.8	1.16619	[-3, -1, -2, 0, 1, -1, -1, 1, -1, -1]
+trivialised	-0.8	1.6	[-2, 0, -2, 1, -1, 0, 1, 1, -4, -2]
+trivialises	-1.1	0.53852	[-1, -1, -1, 0, -1, -1, -1, -2, -2, -1]
+trivialising	-1.4	0.66332	[-2, -1, -2, -1, 0, -1, -2, -1, -2, -2]
+trivialities	-1.0	0.63246	[-2, -2, -1, -1, -1, 0, 0, -1, -1, -1]
+triviality	-0.5	1.11803	[-1, -1, -2, 0, -1, -1, 2, -1, 1, -1]
+trivialization	-0.9	1.04403	[-1, 2, -1, -1, -2, -2, -1, -1, -1, -1]
+trivializations	-0.7	1.18743	[-2, -1, -1, -2, 1, -1, -1, -1, 2, -1]
+trivialize	-1.1	0.53852	[0, -2, -2, -1, -1, -1, -1, -1, -1, -1]
+trivialized	-0.6	0.8	[-1, -1, 0, 0, -1, -1, 1, -1, 0, -2]
+trivializes	-1.0	0.7746	[-1, -1, -1, 0, -1, 0, -1, -1, -1, -3]
+trivializing	-0.6	1.95959	[-1, -1, -2, -1, -1, 2, -2, -4, 1, 3]
+trivially	0.4	1.56205	[-1, -1, -1, -1, 0, 3, 0, 2, 3, 0]
+trivium	-0.3	0.64031	[0, 0, -2, 0, 0, 0, 0, -1, 0, 0]
+trouble	-1.7	0.64031	[-2, -2, -1, -1, -3, -2, -1, -2, -1, -2]
+troubled	-2.0	0.44721	[-2, -2, -2, -1, -2, -3, -2, -2, -2, -2]
+troublemaker	-2.0	0.63246	[-3, -2, -3, -2, -2, -1, -1, -2, -2, -2]
+troublemakers	-2.2	0.74833	[-3, -3, -3, -1, -3, -1, -2, -2, -2, -2]
+troublemaking	-1.8	0.6	[-2, -1, -1, -2, -2, -2, -3, -2, -1, -2]
+troubler	-1.4	0.4899	[-1, -1, -2, -1, -1, -1, -2, -2, -2, -1]
+troublers	-1.9	0.3	[-2, -2, -2, -2, -1, -2, -2, -2, -2, -2]
+troubles	-2.0	0.44721	[-2, -2, -2, -1, -2, -3, -2, -2, -2, -2]
+troubleshoot	0.8	0.9798	[0, 0, 0, 2, 2, 2, 2, 0, 0, 0]
+troubleshooter	1.0	0.89443	[0, 0, 0, 1, 2, 2, 0, 1, 2, 2]
+troubleshooters	0.8	0.87178	[0, 0, 1, 2, 0, 1, 0, 2, 2, 0]
+troubleshooting	0.7	1.34536	[0, 2, 1, 1, -1, 2, 0, 2, -2, 2]
+troubleshoots	0.5	0.92195	[1, -1, 0, 0, 0, 0, 1, 0, 2, 2]
+troublesome	-2.3	0.78102	[-3, -2, -3, -2, -3, -3, -1, -2, -1, -3]
+troublesomely	-1.8	0.6	[-3, -1, -2, -2, -1, -2, -2, -2, -2, -1]
+troublesomeness	-1.9	0.7	[-2, -1, -2, -3, -2, -3, -1, -2, -1, -2]
+troubling	-2.5	0.67082	[-3, -3, -3, -3, -1, -2, -3, -2, -3, -2]
+troublous	-2.1	0.53852	[-2, -2, -2, -2, -2, -3, -2, -3, -1, -2]
+troublously	-2.1	1.22066	[-2, -3, -3, -3, -2, -1, 1, -2, -3, -3]
+trueness	2.1	0.9434	[2, 1, 1, 3, 3, 4, 2, 1, 2, 2]
+truer	1.5	0.67082	[1, 2, 1, 2, 1, 1, 2, 1, 3, 1]
+truest	1.9	0.83066	[2, 2, 2, 3, 3, 0, 2, 1, 2, 2]
+truly	1.9	0.9434	[4, 3, 1, 2, 2, 1, 1, 1, 2, 2]
+trust	2.3	1.26886	[0, 4, 3, 3, 4, 1, 2, 2, 1, 3]
+trustability	2.1	0.7	[1, 3, 3, 2, 2, 2, 1, 3, 2, 2]
+trustable	2.3	0.45826	[2, 2, 3, 2, 2, 3, 3, 2, 2, 2]
+trustbuster	-0.5	1.28452	[-3, -1, 0, 0, 0, 0, -2, 0, 2, -1]
+trusted	2.1	0.9434	[3, 2, 2, 1, 4, 1, 2, 2, 3, 1]
+trustee	1.0	0.89443	[2, 2, 0, 1, 1, 0, 2, 0, 2, 0]
+trustees	0.3	0.64031	[0, 1, 0, 0, 2, 0, 0, 0, 0, 0]
+trusteeship	0.5	0.67082	[0, 1, 1, 0, 0, 1, 0, 0, 2, 0]
+trusteeships	0.6	1.0198	[3, 0, 0, 0, 0, 0, 0, 2, 1, 0]
+truster	1.9	1.3	[2, 2, 1, 1, 4, 0, 3, 1, 4, 1]
+trustful	2.1	0.9434	[1, 2, 2, 1, 2, 2, 1, 3, 3, 4]
+trustfully	1.5	0.67082	[2, 1, 2, 1, 1, 3, 1, 2, 1, 1]
+trustfulness	2.1	0.83066	[3, 2, 3, 2, 3, 2, 2, 2, 0, 2]
+trustier	1.3	1.1	[1, 1, 1, 2, 0, 0, 3, 0, 3, 2]
+trusties	1.0	0.7746	[1, 1, 0, 2, 1, 0, 2, 0, 1, 2]
+trustiest	2.2	0.87178	[3, 2, 2, 3, 2, 2, 4, 1, 1, 2]
+trustily	1.6	0.91652	[2, 0, 3, 1, 2, 1, 1, 1, 2, 3]
+trustiness	1.6	0.91652	[2, 3, 0, 1, 2, 2, 2, 2, 0, 2]
+trusting	1.7	1.00499	[3, 0, 1, 2, 3, 0, 2, 2, 2, 2]
+trustingly	1.6	0.91652	[3, 1, 2, 3, 2, 2, 0, 1, 1, 1]
+trustingness	1.6	1.2	[1, 2, 1, 3, 2, 1, 4, 2, 0, 0]
+trustless	-2.3	0.78102	[-2, -4, -3, -2, -2, -3, -2, -2, -1, -2]
+trustor	0.4	0.66332	[2, 0, 0, 1, 0, 0, 0, 1, 0, 0]
+trustors	1.2	0.87178	[0, 0, 2, 1, 1, 2, 2, 2, 0, 2]
+trusts	2.1	0.53852	[2, 2, 2, 2, 1, 2, 2, 3, 2, 3]
+trustworthily	2.3	0.9	[3, 1, 2, 2, 2, 1, 3, 4, 3, 2]
+trustworthiness	1.8	0.74833	[2, 1, 3, 1, 2, 2, 1, 2, 3, 1]
+trustworthy	2.6	0.91652	[3, 2, 3, 4, 2, 4, 2, 3, 1, 2]
+trusty	2.2	0.74833	[3, 2, 3, 1, 2, 2, 3, 2, 1, 3]
+truth	1.3	1.00499	[2, 1, 0, 1, 1, 0, 3, 3, 1, 1]
+truthful	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
+truthfully	1.9	1.04403	[3, 1, 3, 0, 2, 1, 3, 2, 1, 3]
+truthfulness	1.7	1.1	[3, 2, 2, 2, 1, -1, 3, 2, 2, 1]
+truths	1.8	0.87178	[0, 1, 1, 3, 2, 2, 3, 2, 2, 2]
+tumor	-1.6	1.49666	[-3, -2, -2, -1, -2, 1, -4, 1, -2, -2]
+turmoil	-1.5	0.92195	[-1, -1, -3, -3, -2, -2, -1, -1, 0, -1]
+twat	-3.4	0.91652	[-3, -4, -4, -4, -3, -1, -4, -4, -3, -4]
+ugh	-1.8	0.9798	[-1, -1, -1, -1, -1, -2, -4, -2, -3, -2]
+uglier	-2.2	0.87178	[-2, -2, -1, -3, -4, -1, -3, -2, -2, -2]
+uglies	-2.0	0.89443	[-2, -2, -1, -3, -4, -1, -2, -2, -1, -2]
+ugliest	-2.8	0.74833	[-3, -3, -4, -3, -3, -3, -3, -3, -1, -2]
+uglification	-2.2	0.87178	[-3, -1, -2, -2, -1, -2, -4, -3, -2, -2]
+uglified	-1.5	0.67082	[-1, -1, -3, -2, -2, -1, -1, -1, -2, -1]
+uglifies	-1.8	0.74833	[-1, -1, -3, -2, -3, -1, -2, -2, -2, -1]
+uglify	-2.1	0.9434	[-3, -3, -1, -4, -2, -2, -1, -2, -1, -2]
+uglifying	-2.2	0.4	[-3, -2, -2, -2, -2, -2, -2, -2, -3, -2]
+uglily	-2.1	0.3	[-3, -2, -2, -2, -2, -2, -2, -2, -2, -2]
+ugliness	-2.7	0.9	[-4, -2, -3, -2, -4, -2, -4, -2, -2, -2]
+uglinesses	-2.5	1.0247	[-3, -3, -2, -1, -1, -3, -2, -2, -4, -4]
+ugly	-2.3	0.9	[-3, -2, -1, -2, -4, -1, -3, -2, -2, -3]
+unacceptable	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -3, -2, -2]
+unappreciated	-1.7	0.78102	[-1, -3, -2, -1, -1, -1, -2, -1, -2, -3]
+unapproved	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -1]
+unattractive	-1.9	0.53852	[-1, -2, -3, -2, -1, -2, -2, -2, -2, -2]
+unaware	-0.8	0.4	[-1, -1, -1, 0, -1, -1, 0, -1, -1, -1]
+unbelievable	0.8	1.6	[0, 0, 1, -2, 1, 3, 1, 0, 4, 0]
+unbelieving	-0.8	0.4	[0, -1, -1, -1, -1, -1, -1, 0, -1, -1]
+unbiased	-0.1	1.22066	[-2, -1, 2, 1, 0, -1, -1, 1, 1, -1]
+uncertain	-1.2	0.6	[-2, -1, -2, -1, -1, -1, 0, -1, -2, -1]
+uncertainly	-1.4	0.4899	[-2, -1, -1, -1, -2, -1, -1, -2, -2, -1]
+uncertainness	-1.3	0.45826	[-2, -2, -1, -1, -1, -1, -1, -2, -1, -1]
+uncertainties	-1.4	0.66332	[-3, -2, -1, -1, -1, -1, -1, -2, -1, -1]
+uncertainty	-1.4	0.4899	[-1, -1, -2, -1, -2, -1, -2, -1, -2, -1]
+unclear	-1.0	0.44721	[-2, -1, 0, -1, -1, -1, -1, -1, -1, -1]
+uncomfortable	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -2]
+uncomfortably	-1.7	0.64031	[-2, -1, -3, -1, -1, -2, -2, -1, -2, -2]
+uncompelling	-0.9	0.7	[0, -2, -1, 0, -1, -1, -1, 0, -1, -2]
+unconcerned	-0.9	0.83066	[-2, -2, -1, 1, -1, -1, -1, 0, -1, -1]
+unconfirmed	-0.5	0.67082	[0, -1, 0, -1, 0, -1, 0, 0, -2, 0]
+uncontrollability	-1.7	0.45826	[-1, -1, -2, -2, -2, -2, -1, -2, -2, -2]
+uncontrollable	-1.5	1.11803	[-2, -1, -1, -2, -1, -1, 1, -2, -3, -3]
+uncontrollably	-1.5	0.67082	[-2, -1, 0, -2, -1, -1, -2, -2, -2, -2]
+uncontrolled	-1.0	0.7746	[-1, 0, -1, -2, -1, 0, -1, -2, -2, 0]
+unconvinced	-1.6	0.8	[-2, -3, -1, -2, -1, 0, -2, -2, -1, -2]
+uncredited	-1.0	1.09545	[-1, -2, -2, 2, -1, -2, -1, -1, -1, -1]
+undecided	-0.9	0.9434	[-1, 0, -1, 0, -1, -1, -2, 0, -3, 0]
+underestimate	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -1]
+underestimated	-1.1	0.53852	[-1, -1, -1, -2, 0, -1, -2, -1, -1, -1]
+underestimates	-1.1	1.64012	[-2, -4, -1, -1, -1, -1, 3, -1, -2, -1]
+undermine	-1.2	1.16619	[-2, -2, -1, -1, -1, -1, 2, -2, -2, -2]
+undermined	-1.5	0.67082	[-1, -2, -1, -3, -1, -1, -1, -2, -2, -1]
+undermines	-1.4	0.4899	[-1, -2, -1, -2, -1, -1, -1, -2, -2, -1]
+undermining	-1.5	0.67082	[-1, -3, -1, -2, -2, -1, -1, -1, -2, -1]
+undeserving	-1.9	0.3	[-2, -2, -1, -2, -2, -2, -2, -2, -2, -2]
+undesirable	-1.9	0.7	[-1, -2, -3, -1, -3, -2, -1, -2, -2, -2]
+unease	-1.7	0.64031	[-2, -2, -2, -1, -1, -2, -1, -3, -1, -2]
+uneasier	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -1]
+uneasiest	-2.1	0.83066	[-1, -4, -3, -2, -2, -2, -2, -2, -1, -2]
+uneasily	-1.4	1.0198	[-2, -2, -1, -1, -2, 1, -3, -1, -2, -1]
+uneasiness	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -1, -2]
+uneasinesses	-1.8	0.87178	[-2, -1, -4, -1, -1, -2, -2, -2, -1, -2]
+uneasy	-1.6	0.4899	[-1, -2, -2, -1, -1, -2, -2, -1, -2, -2]
+unemployment	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -1, -2, -2, -3]
+unequal	-1.4	0.66332	[-1, -2, -2, -2, -1, -1, -2, 0, -2, -1]
+unequaled	0.5	1.80278	[-2, 3, 0, 3, 3, 0, 0, 0, -2, 0]
+unethical	-2.3	0.78102	[-3, -3, -1, -2, -2, -2, -3, -1, -3, -3]
+unfair	-2.1	0.83066	[-1, -3, -3, -2, -3, -1, -2, -3, -1, -2]
+unfocused	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -3, -2, -1, -2]
+unfortunate	-2.0	0.63246	[-2, -2, -2, -3, -3, -1, -2, -1, -2, -2]
+unfortunately	-1.4	0.91652	[-2, -1, -2, -2, 1, -2, -1, -1, -2, -2]
+unfortunates	-1.9	0.7	[-2, -3, -1, -1, -2, -2, -2, -1, -3, -2]
+unfriendly	-1.5	0.5	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -1]
+unfulfilled	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -1, -2, -2]
+ungrateful	-2.0	0.0	[-2, -2, -2, -2, -2, -2, -2, -2, -2, -2]
+ungratefully	-1.8	0.6	[-2, -2, -1, -2, -2, -1, -3, -1, -2, -2]
+ungratefulness	-1.6	0.4899	[-2, -2, -2, -2, -1, -1, -1, -2, -2, -1]
+unhappier	-2.4	0.8	[-2, -2, -1, -4, -3, -3, -2, -2, -2, -3]
+unhappiest	-2.5	0.80623	[-3, -4, -3, -2, -1, -3, -2, -2, -2, -3]
+unhappily	-1.9	0.53852	[-2, -1, -2, -2, -3, -2, -1, -2, -2, -2]
+unhappiness	-2.4	0.66332	[-3, -2, -2, -3, -2, -2, -3, -1, -3, -3]
+unhappinesses	-2.2	0.87178	[-3, -4, -2, -2, -2, -2, -1, -2, -1, -3]
+unhappy	-1.8	0.6	[-2, -2, -1, -3, -2, -2, -2, -1, -2, -1]
+unhealthy	-2.4	0.66332	[-1, -2, -3, -3, -2, -3, -3, -2, -2, -3]
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+unimportant	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -1, -2, -1]
+unimpressed	-1.4	0.66332	[-1, -1, -1, -2, -1, -2, -1, -1, -3, -1]
+unimpressive	-1.4	0.4899	[-1, -2, -2, -1, -1, -2, -2, -1, -1, -1]
+unintelligent	-2.0	1.18322	[-1, -2, -3, -1, -1, -4, -1, -1, -4, -2]
+uninvolved	-2.2	0.9798	[-2, -1, -3, -2, -1, -3, -1, -2, -4, -3]
+uninvolving	-2.0	1.18322	[-4, -1, -3, -2, -1, -4, -1, -1, -2, -1]
+united	1.8	0.6	[1, 2, 2, 2, 1, 2, 2, 1, 2, 3]
+unjust	-2.3	0.45826	[-3, -3, -2, -2, -2, -2, -3, -2, -2, -2]
+unkind	-1.6	0.66332	[-2, -2, -1, -1, -1, -2, -3, -1, -1, -2]
+unlovable	-2.7	0.9	[-4, -2, -1, -3, -3, -3, -4, -2, -3, -2]
+unloved	-1.9	0.53852	[-1, -2, -2, -1, -2, -2, -3, -2, -2, -2]
+unlovelier	-1.9	0.7	[-2, -2, -1, -3, -1, -2, -1, -3, -2, -2]
+unloveliest	-1.9	0.83066	[-2, -4, -2, -2, -1, -1, -1, -2, -2, -2]
+unloveliness	-2.0	0.89443	[-2, -3, -1, -1, -3, -1, -3, -2, -3, -1]
+unlovely	-2.1	0.53852	[-2, -3, -2, -3, -1, -2, -2, -2, -2, -2]
+unloving	-2.3	0.45826	[-2, -3, -2, -3, -2, -2, -2, -3, -2, -2]
+unmatched	-0.3	2.0025	[0, -1, 2, 3, 0, -1, -3, 0, -4, 1]
+unmotivated	-1.4	0.4899	[-2, -2, -1, -1, -1, -2, -2, -1, -1, -1]
+unpleasant	-2.1	0.53852	[-2, -2, -3, -3, -2, -2, -2, -2, -1, -2]
+unprofessional	-2.3	0.78102	[-2, -1, -3, -3, -2, -1, -3, -2, -3, -3]
+unprotected	-1.5	0.67082	[-2, -2, -1, -1, -3, -1, -1, -2, -1, -1]
+unresearched	-1.1	0.7	[-2, -1, -1, -1, -1, -2, -2, 0, 0, -1]
+unsatisfied	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -3, -1, -2, -2]
+unsavory	-1.9	0.53852	[-2, -1, -2, -2, -2, -3, -1, -2, -2, -2]
+unsecured	-1.6	0.4899	[-1, -2, -2, -1, -1, -2, -1, -2, -2, -2]
+unsettled	-1.3	0.45826	[-1, -1, -1, -2, -2, -1, -2, -1, -1, -1]
+unsophisticated	-1.2	0.87178	[-1, -1, -1, -2, -2, -2, -1, -2, 1, -1]
+unstable	-1.5	0.5	[-2, -2, -1, -2, -1, -1, -1, -2, -2, -1]
+unstoppable	-0.8	1.77764	[0, -4, 2, 0, 1, -2, -2, 0, -3, 0]
+unsuccessful	-1.5	0.5	[-2, -1, -1, -2, -2, -1, -1, -1, -2, -2]
+unsuccessfully	-1.7	0.78102	[-2, -2, -1, -1, -1, -2, -3, -3, -1, -1]
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+unsure	-1.0	0.44721	[-1, -1, -1, -1, 0, -2, -1, -1, -1, -1]
+unsurely	-1.3	0.78102	[-1, 0, -1, -1, -1, -3, -1, -2, -2, -1]
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+unwelcome	-1.7	0.45826	[-2, -2, -2, -1, -1, -2, -2, -1, -2, -2]
+unworthy	-2.0	0.44721	[-3, -2, -2, -2, -2, -2, -1, -2, -2, -2]
+upset	-1.6	0.4899	[-1, -1, -2, -2, -1, -1, -2, -2, -2, -2]
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+upsetter	-1.9	0.7	[-2, -2, -1, -1, -3, -2, -3, -1, -2, -2]
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+upsetting	-2.1	0.53852	[-2, -3, -2, -3, -2, -1, -2, -2, -2, -2]
+uptight	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -2]
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+uselessly	-1.5	0.67082	[-2, -3, -1, -1, -1, -1, -2, -2, -1, -1]
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+validate	1.5	0.92195	[1, 2, 1, 1, 1, 3, 1, 3, 0, 2]
+validated	0.9	0.83066	[2, 1, 0, 1, 1, 0, 2, 0, 0, 2]
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+vibrant	2.4	0.8	[2, 3, 1, 1, 3, 3, 3, 2, 3, 3]
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+viciously	-1.3	1.26886	[-2, -3, -1, -2, -2, -1, -1, 2, -1, -2]
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+victim	-1.1	1.92094	[-1, -2, 2, -3, -3, -2, -3, 1, 2, -2]
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+victimised	-1.5	1.56525	[-2, -2, -2, 1, -3, 2, -2, -3, -2, -2]
+victimises	-1.2	2.31517	[-3, -3, -4, 2, -2, -2, 1, 2, 1, -4]
+victimising	-2.5	0.67082	[-3, -1, -3, -2, -2, -3, -3, -2, -3, -3]
+victimization	-2.3	0.78102	[-1, -3, -3, -2, -3, -1, -3, -2, -3, -2]
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+victimizer	-1.8	1.72047	[-3, -2, -3, -3, -2, 2, 1, -2, -3, -3]
+victimizers	-1.6	1.68523	[-3, -2, -3, 1, -3, -1, -2, 2, -2, -3]
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+victimizing	-2.6	0.4899	[-2, -3, -3, -3, -2, -3, -2, -3, -2, -3]
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+villainously	-2.9	0.53852	[-3, -3, -3, -3, -3, -4, -2, -3, -2, -3]
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+vindicating	-1.1	1.97231	[-3, -2, 2, -3, -2, 1, 1, 1, -3, -3]
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+warmly	1.7	0.64031	[2, 1, 2, 1, 2, 1, 2, 1, 2, 3]
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+wasting	-1.7	0.9	[-3, -1, -2, -2, -1, -2, -3, 0, -1, -2]
+wavering	-0.6	1.0198	[-1, -1, 0, 0, -1, -1, -1, 2, -1, -2]
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+weaken	-1.8	0.6	[-2, -2, -2, -1, -1, -3, -2, -2, -1, -2]
+weakened	-1.3	0.9	[-2, -1, -1, -1, -1, -2, -2, -2, 1, -2]
+weakener	-1.6	1.11355	[-2, -1, -1, -1, -2, -2, -3, -3, 1, -2]
+weakeners	-1.3	0.45826	[-1, -2, -1, -2, -1, -1, -2, -1, -1, -1]
+weakening	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+weakens	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -1, -2, -1, -2]
+weaker	-1.9	0.83066	[-2, -2, -2, -2, -2, -1, -4, -1, -1, -2]
+weakest	-2.3	0.64031	[-2, -4, -2, -3, -2, -2, -2, -2, -2, -2]
+weakfish	-0.2	1.07703	[0, -2, 0, 0, 0, 0, -2, 0, 2, 0]
+weakfishes	-0.6	0.8	[0, -1, 0, -2, 0, 0, -1, 0, -2, 0]
+weakhearted	-1.6	0.8	[-1, -3, -1, -1, -2, -1, -3, -2, -1, -1]
+weakish	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
+weaklier	-1.5	0.67082	[-1, -2, -1, -3, -2, -1, -1, -2, -1, -1]
+weakliest	-2.1	0.83066	[-2, -2, -2, -2, -3, -1, -2, -1, -4, -2]
+weakling	-1.3	1.00499	[-1, -2, -1, -3, -2, -2, -1, -1, 1, -1]
+weaklings	-1.4	0.66332	[-2, -1, -1, -1, -1, -2, -2, 0, -2, -2]
+weakly	-1.8	0.87178	[-2, -2, -2, -2, -4, -1, -1, -1, -1, -2]
+weakness	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -1, -3, -2, -2]
+weaknesses	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -1, -2]
+weakside	-1.1	1.37477	[-3, -2, -3, -1, -2, -1, 1, 1, -1, 0]
+wealth	2.2	0.4	[2, 3, 2, 2, 2, 3, 2, 2, 2, 2]
+wealthier	2.2	0.6	[3, 2, 1, 3, 2, 2, 2, 3, 2, 2]
+wealthiest	2.2	0.9798	[2, 4, 4, 1, 2, 1, 2, 2, 2, 2]
+wealthily	2.0	0.89443	[2, 3, 1, 4, 2, 1, 1, 2, 2, 2]
+wealthiness	2.4	1.11355	[2, 4, 2, 4, 1, 2, 4, 1, 2, 2]
+wealthy	1.5	1.0247	[1, 2, 1, 4, 1, 0, 2, 1, 2, 1]
+weapon	-1.2	0.87178	[0, -2, -2, -1, 0, -2, -1, -2, 0, -2]
+weaponed	-1.4	0.91652	[-2, -2, -3, -1, -1, 0, 0, -2, -1, -2]
+weaponless	0.1	1.13578	[2, -1, 0, 0, -1, 1, -1, 0, 2, -1]
+weaponry	-0.9	0.7	[-2, -2, 0, -1, 0, -1, -1, -1, 0, -1]
+weapons	-1.9	0.9434	[-2, -1, -2, -2, -1, -3, -3, -3, -2, 0]
+weary	-1.1	1.13578	[-2, -1, -2, -3, 0, -1, -1, -2, 0, 1]
+weep	-2.7	0.9	[-2, -4, -4, -3, -3, -3, -3, -2, -1, -2]
+weeper	-1.9	0.53852	[-2, -2, -2, -3, -1, -1, -2, -2, -2, -2]
+weepers	-1.1	1.13578	[-2, -2, -1, -2, -1, 1, -2, 1, -1, -2]
+weepie	-0.4	0.91652	[0, 1, -1, 0, -1, -2, 0, -1, -1, 1]
+weepier	-1.8	0.87178	[-3, -3, -2, -1, -2, -2, -2, 0, -1, -2]
+weepies	-1.6	0.8	[-2, -3, -2, -1, -1, -2, -2, 0, -1, -2]
+weepiest	-2.4	0.91652	[-4, -2, -2, -2, -2, -1, -2, -2, -4, -3]
+weeping	-1.9	0.9434	[-2, -2, -1, -1, -1, -1, -4, -2, -2, -3]
+weepings	-1.9	0.9434	[-2, -2, -3, 0, -1, -2, -2, -3, -1, -3]
+weeps	-1.4	1.35647	[-2, -3, -1, -2, -1, -3, 1, -2, 1, -2]
+weepy	-1.3	1.55242	[-2, -3, -1, -2, 2, -3, -1, -2, 1, -2]
+weird	-0.7	0.64031	[-1, 0, 0, -1, -1, -1, 0, 0, -2, -1]
+weirder	-0.5	0.80623	[1, -1, -1, -1, -1, 1, -1, -1, 0, -1]
+weirdest	-0.9	1.22066	[-2, 0, -2, -1, -1, -1, -3, 1, 1, -1]
+weirdie	-1.3	0.45826	[-1, -2, -1, -2, -1, -1, -2, -1, -1, -1]
+weirdies	-1.0	0.63246	[0, -1, -1, -1, -1, 0, -2, -2, -1, -1]
+weirdly	-1.2	0.74833	[0, -1, -1, -2, -3, -1, -1, -1, -1, -1]
+weirdness	-0.9	1.64012	[-3, -2, -1, -1, 2, -1, 1, -3, 1, -2]
+weirdnesses	-0.7	1.00499	[-1, -2, 0, -1, -2, 1, -1, -1, -1, 1]
+weirdo	-1.8	0.6	[-2, -2, -2, -2, -2, -2, -1, -1, -3, -1]
+weirdoes	-1.3	0.64031	[-2, -1, -2, -1, -1, -2, -1, 0, -1, -2]
+weirdos	-1.1	0.9434	[-1, -1, -1, -2, 1, -3, -1, -1, -1, -1]
+weirds	-0.6	0.4899	[-1, -1, -1, 0, -1, 0, 0, -1, 0, -1]
+weirdy	-0.9	0.83066	[-1, -1, 0, 0, -1, 0, -2, -2, 0, -2]
+welcome	2.0	0.63246	[1, 3, 2, 1, 2, 2, 2, 2, 3, 2]
+welcomed	1.4	0.4899	[1, 1, 2, 2, 1, 2, 1, 2, 1, 1]
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+welcomeness	2.0	0.89443	[2, 3, 1, 2, 3, 0, 2, 3, 2, 2]
+welcomer	1.4	0.4899	[1, 1, 2, 2, 2, 2, 1, 1, 1, 1]
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+welcomes	1.7	0.78102	[1, 1, 2, 2, 3, 3, 1, 2, 1, 1]
+welcoming	1.9	0.7	[2, 2, 1, 1, 2, 2, 2, 3, 3, 1]
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+wellaway	-0.8	1.98997	[3, -2, -3, -3, -1, -2, 1, -2, -1, 2]
+wellborn	1.8	0.74833	[2, 1, 2, 1, 2, 2, 1, 3, 1, 3]
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+welled	0.4	0.8	[0, 0, 2, 0, 0, 0, 0, 0, 2, 0]
+wellhead	0.1	0.3	[0, 0, 1, 0, 0, 0, 0, 0, 0, 0]
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+wellies	0.4	0.4899	[0, 1, 0, 0, 0, 1, 0, 0, 1, 1]
+welling	1.6	0.8	[2, 0, 1, 2, 2, 1, 3, 2, 2, 1]
+wellness	1.9	0.9434	[1, 2, 2, 1, 2, 1, 1, 3, 4, 2]
+wells	1.0	1.0	[2, 0, 3, 0, 1, 0, 2, 1, 1, 0]
+wellsite	0.5	0.67082	[0, 0, 1, 2, 0, 0, 0, 0, 1, 1]
+wellspring	1.5	0.92195	[3, 1, 1, 1, 0, 2, 2, 3, 1, 1]
+wellsprings	1.4	0.8	[1, 0, 0, 2, 2, 2, 1, 2, 2, 2]
+welly	0.2	0.4	[0, 0, 0, 1, 0, 1, 0, 0, 0, 0]
+wept	-2.0	1.09545	[-3, -2, -3, -3, -1, -3, 0, -1, -1, -3]
+whimsical	0.3	1.61555	[2, 1, 1, 2, -1, 1, -3, -2, 1, 1]
+whine	-1.5	1.11803	[-1, -4, -1, -1, -1, -3, 0, -2, -1, -1]
+whined	-0.9	1.04403	[-2, -1, -2, -1, -1, -1, -2, 1, 1, -1]
+whiner	-1.2	0.4	[-1, -2, -1, -1, -1, -2, -1, -1, -1, -1]
+whiners	-0.6	1.95959	[-2, 0, -2, -2, 4, 1, 1, -2, -2, -2]
+whines	-1.8	0.6	[-2, -2, -2, -1, -2, -2, -3, -1, -2, -1]
+whiney	-1.3	0.45826	[-1, -2, -1, -1, -1, -2, -2, -1, -1, -1]
+whining	-0.9	1.51327	[-3, 0, -1, -1, -3, -1, 1, 2, -2, -1]
+whitewash	0.1	0.7	[-1, 0, 1, -1, 0, 0, 0, 1, 1, 0]
+whore	-3.3	0.64031	[-4, -4, -3, -2, -3, -4, -3, -3, -4, -3]
+whored	-2.8	0.87178	[-2, -3, -4, -2, -2, -3, -4, -4, -2, -2]
+whoredom	-2.1	2.02237	[-4, -2, -4, -3, -3, -3, -4, -1, 2, 1]
+whoredoms	-2.4	1.11355	[-1, -3, 0, -3, -2, -3, -3, -4, -2, -3]
+whorehouse	-1.1	2.11896	[-2, -2, -2, 3, 3, -3, -3, -2, -1, -2]
+whorehouses	-1.9	1.92094	[-4, -3, -4, -3, 0, 0, -3, 2, -1, -3]
+whoremaster	-1.9	1.22066	[-1, -3, -3, -2, -1, -3, 0, 0, -3, -3]
+whoremasters	-1.5	1.85742	[-3, -1, -1, -4, -2, 2, -1, 1, -2, -4]
+whoremonger	-2.6	0.91652	[-3, -1, -3, -3, -3, -3, -3, -1, -4, -2]
+whoremongers	-2.0	1.78885	[-4, -3, 0, -3, -3, -3, -3, 1, 1, -3]
+whores	-3.0	1.0	[-3, -3, -4, -2, -1, -3, -4, -4, -2, -4]
+whoreson	-2.2	1.46969	[-2, -3, -4, -4, -3, -1, -1, 1, -3, -2]
+whoresons	-2.5	1.20416	[-3, -3, -2, -2, 0, -4, -3, -1, -3, -4]
+wicked	-2.4	0.8	[-3, -4, -3, -3, -2, -2, -2, -1, -2, -2]
+wickeder	-2.2	1.32665	[-2, -3, -1, -4, 1, -3, -3, -3, -2, -2]
+wickedest	-2.9	1.04403	[-3, -1, -3, -3, -3, -3, -1, -4, -4, -4]
+wickedly	-2.1	0.83066	[-2, -2, -1, -3, -2, -3, -1, -3, -1, -3]
+wickedness	-2.1	0.83066	[-2, -1, -2, -2, -3, -1, -2, -4, -2, -2]
+wickednesses	-2.2	1.16619	[-1, -2, -4, -2, -3, -1, -3, -4, -1, -1]
+widowed	-2.1	1.22066	[0, -4, -2, -4, -3, -2, -2, -2, -1, -1]
+willingness	1.1	0.7	[0, 2, 1, 1, 2, 2, 1, 0, 1, 1]
+wimp	-1.4	1.28062	[-2, -3, -1, -2, -1, -2, -2, -1, 2, -2]
+wimpier	-1.0	1.18322	[-1, -2, -2, -1, -2, 0, 1, -2, 1, -2]
+wimpiest	-0.9	1.22066	[-3, -1, -2, -1, -2, -1, 1, 1, 0, -1]
+wimpiness	-1.2	0.9798	[1, -1, -3, -1, -2, -1, -1, -1, -2, -1]
+wimpish	-1.6	0.4899	[-2, -1, -2, -1, -2, -2, -1, -2, -2, -1]
+wimpishness	-0.2	1.249	[-3, -1, 0, -1, -1, 1, 1, 1, 1, 0]
+wimple	-0.2	0.74833	[0, -1, 0, 0, 0, 0, -2, 0, 0, 1]
+wimples	-0.3	0.78102	[-2, 0, 0, 0, 0, -1, 0, -1, 1, 0]
+wimps	-1.0	1.18322	[-2, -2, -1, -1, 0, -2, -2, 1, -2, 1]
+wimpy	-0.9	1.04403	[-2, -1, -1, -1, -1, -2, -1, 1, -2, 1]
+win	2.8	0.87178	[3, 2, 4, 3, 2, 4, 3, 1, 3, 3]
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+winner	2.8	0.87178	[2, 2, 2, 3, 4, 2, 3, 4, 2, 4]
+winners	2.1	1.44568	[3, 3, 2, 3, 3, 2, 2, -2, 3, 2]
+winning	2.4	0.4899	[2, 3, 3, 2, 2, 2, 3, 3, 2, 2]
+winningly	2.3	1.48661	[1, 3, 4, 3, 3, 1, 2, 3, -1, 4]
+winnings	2.5	0.92195	[3, 4, 3, 2, 2, 3, 1, 1, 3, 3]
+winnow	-0.3	1.00499	[0, -1, 0, -2, 1, 1, -2, 0, 0, 0]
+winnower	-0.1	0.3	[0, 0, 0, 0, 0, -1, 0, 0, 0, 0]
+winnowers	-0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, -2, 0]
+winnowing	-0.1	0.53852	[0, 0, -1, 0, 0, 0, 0, 1, -1, 0]
+winnows	-0.2	0.4	[0, 0, -1, -1, 0, 0, 0, 0, 0, 0]
+wins	2.7	0.78102	[2, 2, 3, 3, 4, 4, 3, 2, 2, 2]
+wisdom	2.4	0.66332	[2, 3, 4, 2, 3, 2, 2, 2, 2, 2]
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+wiseacre	-1.2	1.16619	[-2, -1, -2, -2, -2, -1, -2, 1, 1, -2]
+wiseacres	-0.1	0.9434	[-2, 1, 0, -1, 0, 1, 1, -1, 0, 0]
+wiseass	-1.8	0.6	[-2, -2, -1, -1, -2, -2, -3, -2, -1, -2]
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+wisecrack	-0.1	1.22066	[-1, -1, -1, -2, 2, 1, -1, 1, 1, 0]
+wisecracked	-0.5	0.92195	[1, 1, -1, -1, 0, -1, -2, 0, -1, -1]
+wisecracker	-0.1	0.7	[-1, 1, -1, -1, 0, 0, 0, 0, 1, 0]
+wisecrackers	0.1	1.04403	[-1, 0, 1, 1, 0, 2, 1, -1, -1, -1]
+wisecracking	-0.6	0.4899	[0, 0, -1, 0, -1, 0, -1, -1, -1, -1]
+wisecracks	-0.3	1.55242	[1, 2, -1, 2, -3, 0, 0, -2, -1, -1]
+wised	1.5	0.67082	[2, 2, 2, 1, 1, 2, 0, 1, 2, 2]
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+wiselier	0.9	1.3	[1, 2, 2, -2, 0, 1, 3, 1, 0, 1]
+wiseliest	1.6	1.49666	[1, 4, 2, 2, 1, 2, 2, 3, -2, 1]
+wisely	1.8	0.6	[1, 2, 3, 2, 1, 2, 2, 1, 2, 2]
+wiseness	1.9	0.7	[2, 3, 2, 2, 3, 1, 1, 1, 2, 2]
+wisenheimer	-1.0	1.18322	[-1, 1, -1, -1, -1, 0, -1, -3, 0, -3]
+wisenheimers	-1.4	0.91652	[-3, -3, -2, -1, -1, -1, 0, -1, -1, -1]
+wisents	0.4	0.91652	[0, 0, 0, 0, 1, 0, 0, 0, 3, 0]
+wiser	1.2	0.87178	[1, 3, 0, 1, 1, 2, 0, 2, 1, 1]
+wises	1.3	1.48661	[3, 3, 2, -2, 2, 0, 0, 2, 2, 1]
+wisest	2.1	1.51327	[1, 3, 3, 3, 3, 2, 2, 3, -2, 3]
+wisewomen	1.3	0.9	[2, 2, 0, 0, 2, 0, 1, 2, 2, 2]
+wish	1.7	1.1	[2, 1, 1, 0, 2, 1, 3, 2, 4, 1]
+wishes	0.6	0.8	[0, 0, 1, 0, 1, 0, 2, 0, 2, 0]
+wishing	0.9	0.7	[2, 1, 1, 0, 0, 0, 1, 1, 2, 1]
+witch	-1.5	0.80623	[-1, -2, -2, -1, -3, 0, -2, -2, -1, -1]
+withdrawal	0.1	1.57797	[1, -1, 0, -2, -2, 2, -1, 1, 0, 3]
+woe	-1.8	0.6	[-3, -2, -2, -2, -1, -1, -2, -1, -2, -2]
+woebegone	-2.6	0.66332	[-3, -2, -3, -2, -2, -4, -3, -2, -2, -3]
+woebegoneness	-1.1	1.37477	[-3, 0, -1, 1, -1, -4, 0, -1, -1, -1]
+woeful	-1.9	0.83066	[-1, -2, -2, -1, -3, -3, -1, -2, -1, -3]
+woefully	-1.7	1.48661	[-1, -3, -2, 1, -3, -3, -2, -2, 1, -3]
+woefulness	-2.1	0.7	[-3, -2, -2, -1, -2, -3, -3, -1, -2, -2]
+woes	-1.9	0.83066	[-2, -2, -2, -1, -2, -3, -3, 0, -2, -2]
+woesome	-1.2	1.6	[-2, -3, -2, -1, 0, 3, -2, -2, -1, -2]
+won	2.7	0.9	[3, 4, 2, 2, 2, 4, 4, 2, 2, 2]
+wonderful	2.7	0.78102	[2, 3, 3, 2, 4, 2, 2, 3, 4, 2]
+wonderfully	2.9	0.83066	[1, 3, 3, 4, 3, 2, 3, 3, 4, 3]
+wonderfulness	2.9	0.53852	[3, 2, 3, 3, 3, 3, 3, 2, 4, 3]
+woo	2.1	1.37477	[4, 2, 1, 3, 2, 2, -1, 2, 2, 4]
+woohoo	2.3	1.1	[3, 3, 1, 4, 4, 2, 1, 1, 2, 2]
+woot	1.8	1.07703	[2, 0, 2, 2, 2, 2, 0, 4, 2, 2]
+worn	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -2, -1]
+worried	-1.2	0.74833	[-1, -1, -1, -1, -1, -2, -3, 0, -1, -1]
+worriedly	-2.0	0.44721	[-2, -2, -3, -2, -2, -2, -2, -1, -2, -2]
+worrier	-1.8	0.6	[-2, -2, -1, -2, -1, -3, -2, -2, -1, -2]
+worriers	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -1, -2, -1, -2]
+worries	-1.8	0.6	[-2, -2, -1, -2, -1, -2, -2, -3, -1, -2]
+worriment	-1.5	0.67082	[-1, -2, -1, -1, -1, -2, -1, -3, -1, -2]
+worriments	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -3, -1, -2, -2]
+worrisome	-1.7	0.64031	[-1, -1, -1, -2, -1, -2, -3, -2, -2, -2]
+worrisomely	-2.0	0.63246	[-1, -2, -1, -2, -2, -3, -2, -2, -3, -2]
+worrisomeness	-1.9	0.53852	[-2, -2, -3, -1, -2, -2, -2, -1, -2, -2]
+worrit	-2.1	0.53852	[-2, -2, -1, -2, -2, -3, -3, -2, -2, -2]
+worrits	-1.2	0.9798	[-1, -2, -2, -1, 0, 0, -1, -3, 0, -2]
+worry	-1.9	0.7	[-2, -3, -1, -3, -1, -2, -1, -2, -2, -2]
+worrying	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -1, -1, -2, -2]
+worrywart	-1.8	0.9798	[-2, -2, -2, -1, -1, -1, -1, -3, -1, -4]
+worrywarts	-1.5	0.5	[-2, -1, -2, -2, -2, -1, -1, -1, -2, -1]
+worse	-2.1	0.83066	[-2, -2, -1, -3, -4, -2, -1, -2, -2, -2]
+worsen	-2.3	0.78102	[-4, -3, -1, -2, -2, -2, -2, -3, -2, -2]
+worsened	-1.9	1.22066	[-2, -2, -2, -1, -2, -2, -4, 1, -3, -2]
+worsening	-2.0	0.44721	[-2, -3, -2, -2, -2, -2, -1, -2, -2, -2]
+worsens	-2.1	0.53852	[-2, -2, -2, -2, -1, -2, -2, -3, -3, -2]
+worser	-2.0	0.89443	[-2, -2, -4, -1, -2, -2, -2, -3, -1, -1]
+worship	1.2	1.07703	[1, 0, 0, 1, 3, 0, 2, 3, 1, 1]
+worshiped	2.4	1.0198	[1, 2, 4, 3, 4, 1, 2, 3, 2, 2]
+worshiper	1.0	1.0	[0, 0, 2, 3, 0, 2, 1, 1, 1, 0]
+worshipers	0.9	0.83066	[0, 0, 0, 2, 1, 1, 1, 2, 2, 0]
+worshipful	0.7	1.00499	[1, -1, 3, 1, 1, 1, 0, 0, 0, 1]
+worshipfully	1.1	1.3	[0, 0, 0, 1, 3, 0, 3, 3, 1, 0]
+worshipfulness	1.6	0.8	[3, 1, 2, 2, 1, 1, 3, 1, 1, 1]
+worshiping	1.0	1.18322	[0, 3, 0, 3, 0, 1, 1, 2, 0, 0]
+worshipless	-0.6	1.0198	[0, -1, -3, -1, -1, -1, 0, 0, 0, 1]
+worshipped	2.7	0.78102	[3, 2, 3, 3, 1, 4, 2, 3, 3, 3]
+worshipper	0.6	0.66332	[1, 1, 0, 0, 1, 0, 0, 2, 1, 0]
+worshippers	0.8	0.87178	[0, 1, 0, 0, 3, 1, 1, 1, 0, 1]
+worshipping	1.6	1.28062	[1, 3, 3, 3, 0, 3, 1, 0, 2, 0]
+worships	1.4	1.11355	[2, 0, 1, 3, 2, 1, 0, 3, 2, 0]
+worst	-3.1	1.04403	[-4, -4, -3, -1, -3, -4, -2, -2, -4, -4]
+worth	0.9	0.9434	[0, 0, 1, 1, 2, 1, 1, 3, 0, 0]
+worthless	-1.9	1.13578	[-3, -1, -3, -4, -1, -3, -1, -1, -1, -1]
+worthwhile	1.4	0.4899	[1, 1, 1, 2, 1, 1, 2, 1, 2, 2]
+worthy	1.9	0.53852	[2, 2, 2, 1, 1, 2, 2, 2, 3, 2]
+wow	2.8	0.9798	[2, 3, 2, 4, 4, 3, 3, 2, 1, 4]
+wowed	2.6	0.8	[3, 3, 4, 3, 2, 1, 3, 3, 2, 2]
+wowing	2.5	0.67082	[2, 2, 3, 3, 2, 3, 4, 2, 2, 2]
+wows	2.0	1.61245	[2, 3, 3, 3, 2, 1, -2, 1, 4, 3]
+wowser	-1.1	2.02237	[-3, 3, 0, 2, -2, -1, -3, -2, -2, -3]
+wowsers	1.0	2.14476	[0, -2, 4, 2, 3, 0, 1, 2, -3, 3]
+wrathful	-2.7	0.64031	[-3, -2, -2, -3, -3, -2, -4, -2, -3, -3]
+wreck	-1.9	0.7	[-1, -2, -3, -3, -2, -2, -2, -1, -1, -2]
+wrong	-2.1	1.04403	[-2, -2, -2, -2, -4, -4, -1, -1, -1, -2]
+wronged	-1.9	0.53852	[-2, -2, -2, -2, -2, -1, -3, -2, -2, -1]
+x-d	2.6	0.91652	[2, 3, 3, 4, 1, 2, 3, 4, 2, 2]
+x-p	1.7	0.45826	[2, 2, 1, 2, 2, 1, 1, 2, 2, 2]
+xd	2.8	0.87178	[3, 3, 4, 2, 3, 3, 1, 2, 4, 3]
+xp	1.6	0.4899	[2, 2, 2, 1, 1, 1, 2, 2, 1, 2]
+yay	2.4	1.0198	[1, 3, 3, 2, 2, 1, 4, 4, 2, 2]
+yeah	1.2	0.6	[1, 1, 1, 2, 1, 1, 0, 2, 1, 2]
+yearning	0.5	1.0247	[0, 1, 0, 1, 0, 3, 0, 1, -1, 0]
+yeees	1.7	1.00499	[1, 3, 1, 2, 1, 1, 4, 2, 1, 1]
+yep	1.2	0.4	[1, 1, 1, 1, 1, 1, 2, 2, 1, 1]
+yes	1.7	0.78102	[1, 2, 2, 1, 1, 1, 3, 3, 1, 2]
+youthful	1.3	0.45826	[1, 2, 1, 2, 1, 1, 1, 1, 2, 1]
+yucky	-1.8	0.6	[-2, -1, -1, -2, -2, -1, -2, -2, -3, -2]
+yummy	2.4	1.0198	[1, 2, 4, 3, 2, 2, 3, 1, 4, 2]
+zealot	-1.9	1.04403	[-2, -3, -1, -2, -1, -3, -4, -1, -1, -1]
+zealots	-0.8	1.83303	[-1, -2, -1, -2, -2, 1, -2, 4, -1, -2]
+zealous	0.5	1.43178	[2, -1, 2, 1, 0, 0, 3, 0, -2, 0]
+{:	1.8	0.9798	[1, 3, 2, 2, 1, 1, 4, 2, 1, 1]
+|-0	-1.2	0.74833	[0, -2, -1, -1, -1, -1, -1, -1, -1, -3]
+|-:	-0.8	0.74833	[-1, -2, 0, -1, 0, -2, -1, -1, 0, 0]
+|-:>	-1.6	0.4899	[-1, -2, -2, -2, -2, -1, -1, -2, -2, -1]
+|-o	-1.2	0.9798	[-1, 0, -1, -1, -1, -1, -1, -4, -1, -1]
+|:	-0.5	1.68819	[2, -3, -1, 0, -1, -1, -1, -2, -1, 3]
+|;-)	2.2	1.32665	[4, 1, 1, 1, 3, 2, 4, 1, 4, 1]
+|=	-0.4	1.56205	[2, -2, -1, 0, -1, -1, -1, -2, -1, 3]
+|^:	-1.1	0.7	[-2, 0, -1, -1, 0, -1, -1, -2, -2, -1]
+|o:	-0.9	0.53852	[-1, 0, -1, -2, -1, 0, -1, -1, -1, -1]
+||-:	-2.3	0.45826	[-2, -2, -2, -3, -3, -3, -2, -2, -2, -2]
+}:	-2.1	0.83066	[-1, -1, -3, -2, -3, -2, -2, -1, -3, -3]
+}:(	-2.0	0.63246	[-3, -1, -2, -1, -3, -2, -2, -2, -2, -2]
+}:)	0.4	1.42829	[1, 1, -2, 1, 2, -2, 1, -1, 2, 1]
+}:-(	-2.1	0.7	[-2, -1, -2, -2, -2, -4, -2, -2, -2, -2]
+}:-)	0.3	1.61555	[1, 1, -2, 1, -1, -3, 2, 2, 1, 1]
\ No newline at end of file