mirror of
https://github.com/gsi-upm/senpy
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Merge branch 'taiger' into 'master'
Taiger Closes #12 See merge request senpy/senpy-plugins-community!1
This commit is contained in:
J. Fernando Sánchez
commit
0e4146ed8d
7
Makefile
7
Makefile
@ -3,19 +3,20 @@ NAME=senpycommunity
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REPO=gsiupm
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PLUGINS= $(filter %/, $(wildcard */))
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IMAGENAME=gsiupm/senpy-plugins-community
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DOCKER_FLAGS=
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DOCKER_FLAGS=-e MOCK_REQUESTS=$(MOCK_REQUESTS)
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DEV_PORT?=5000
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ifdef SENPY_FOLDER
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DOCKER_FLAGS+= -v $(realpath $(SENPY_FOLDER)):/usr/src/app/
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endif
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all: build run
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test-fast:
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test-fast-%:
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docker run $(DOCKER_FLAGS) -v $$PWD/$*:/senpy-plugins/ -v $$PWD/data:/data/ --rm $(IMAGEWTAG) --only-test $(TEST_FLAGS)
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test-fast: test-fast-/
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test: docker-build test-fast
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dev:
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62
sentiment-taiger/README.md
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62
sentiment-taiger/README.md
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@ -0,0 +1,62 @@
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# Senpy Plugin Taiger
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Service that analyzes sentiments from social posts written in Spanish or English.
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## Usage
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To use this plugin, you should use a GET Requests with the following possible params:
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Params:
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- Input: text to analyse.(required)
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- Endpoint: Enpoint to the Taiger service.
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## Example of Usage
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Example request:
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```
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http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-taiger&inputText=This%20is%20amazing
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```
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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.
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For example, this would be the example respond for the request done.
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```
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{
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"@context": "http://localhost:5005/api/contexts/Results.jsonld",
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"@id": "_:Results_1532449339.5887764",
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"@type": "results",
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"analysis": [
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"endpoint:plugins/sentiment-taiger_0.1"
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],
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"entries": [
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{
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"@id": "#",
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"@type": "entry",
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"emotions": [],
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"entities": [],
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"nif:isString": "This is amazing",
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"sentiments": [
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{
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"@id": "Opinion0",
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"@type": "sentiment",
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"marl:hasPolarity": "marl:Positive",
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"marl:polarityValue": -1.4646806570973374,
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"normalizedText": "This is amazing",
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"prov:wasGeneratedBy": "endpoint:plugins/sentiment-taiger_0.1"
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}
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],
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"suggestions": [],
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"topics": []
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}
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]
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}
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```
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As it can be seen, this plugin analyzes sentiment givin three categories or tags: `marl:Positive`, `marl:Neutral` or `marl:Negative`, that will be held in the `marl:hasPolarity` field. Moreover, the plugin retrieves a `marl:polarityValue`.
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This plugin supports **python2.7** and **python3**.
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![alt GSI Logo][logoGSI]
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[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"
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11
sentiment-taiger/docker-compose.yml
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11
sentiment-taiger/docker-compose.yml
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@ -0,0 +1,11 @@
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version: '3'
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services:
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dev:
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image: gsiupm/senpy:latest
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working_dir: "/senpy-plugins"
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ports:
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- "127.0.0.1:5005:5000"
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volumes:
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- ".:/senpy-plugins"
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environment:
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TAIGER_ENDPOINT: 'http://34.244.91.7:8080/sentiment/classifyPositivity'
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176
sentiment-taiger/taiger_plugin.py
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176
sentiment-taiger/taiger_plugin.py
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# -*- coding: utf-8 -*-
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import time
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import requests
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import json
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import string
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import os
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from os import path
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import time
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from senpy.plugins import SentimentPlugin
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from senpy.models import Results, Entry, Entity, Topic, Sentiment, Error
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TAIGER_ENDPOINT = os.environ.get("TAIGER_ENDPOINT", 'http://134.244.91.7:8080/sentiment/classifyPositivity')
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class TaigerPlugin(SentimentPlugin):
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'''
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Service that analyzes sentiments from social posts written in Spanish or English.
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Example request:
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http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-taiger&inputText=This%20is%20amazing
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'''
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name = 'sentiment-taiger'
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author = 'GSI UPM'
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version = "0.1"
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maxPolarityValue = 0
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minPolarityValue = -10
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def _polarity(self, value):
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if 'neu' in value:
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polarity = 'marl:Neutral'
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elif 'neg' in value:
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polarity = 'marl:Negative'
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elif 'pos' in value:
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polarity = 'marl:Positive'
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return polarity
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def analyse_entry(self, entry, params):
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txt = entry['nif:isString']
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api = TAIGER_ENDPOINT
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parameters = {
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'inputText': txt
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}
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try:
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r = requests.get(
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api, params=parameters, timeout=3)
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api_response = r.json()
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except requests.exceptions.Timeout:
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raise Error("No response from the API")
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except Exception as ex:
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raise Error("There was a problem with the endpoint: {}".format(ex))
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if not api_response.get('positivityCategory'):
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raise Error('No positive category in response: {}'.format(r.json()))
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self.log.debug(api_response)
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agg_polarity = self._polarity(api_response.get('positivityCategory'))
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normalized_text = api_response.get('normalizedText', None)
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agg_opinion = Sentiment(
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id="Opinion0",
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marl__hasPolarity=agg_polarity,
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marl__polarityValue=api_response['positivityScore']
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)
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agg_opinion["normalizedText"] = api_response['normalizedText']
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agg_opinion.prov(self)
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entry.sentiments.append(agg_opinion)
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yield entry
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test_cases = [
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{
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'params': {
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'algo': 'sentiment-taiger',
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'intype': 'direct',
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'expanded-jsonld': 0,
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'informat': 'text',
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'prefix': '',
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'plugin_type': 'analysisPlugin',
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'urischeme': 'RFC5147String',
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'outformat': 'json-ld',
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'conversion': 'full',
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'language': 'en',
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'apikey': '00000',
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'algorithm': 'sentiment-taiger'
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},
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'input': 'I hate to say this',
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'expected': {
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'sentiments': [
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{'marl:hasPolarity': 'marl:Negative'}],
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},
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'responses': [
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{
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'url': TAIGER_ENDPOINT,
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'json': {
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"inputText": "I hate to say this",
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"normalizedText": "I hate to say this",
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"positivityScore": -1.8951251587831475,
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"positivityCategory": "neg"
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}
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}
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]
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},
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{
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'params': {
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'algo': 'sentiment-taiger',
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'intype': 'direct',
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'expanded-jsonld': 0,
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'informat': 'text',
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'prefix': '',
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'plugin_type': 'analysisPlugin',
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'urischeme': 'RFC5147String',
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'outformat': 'json-ld',
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'conversion': 'full',
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'language': 'en',
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'apikey': '00000',
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'algorithm': 'sentiment-taiger'
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},
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'input': 'This is amazing',
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'expected': {
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'sentiments': [
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{'marl:hasPolarity': 'marl:Positive'}],
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},
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'responses': [
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{
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'url': TAIGER_ENDPOINT,
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'json': {
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"inputText": "This is amazing ",
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"normalizedText": "This is amazing",
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"positivityScore": -1.4646806570973374,
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"positivityCategory": "pos"
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}
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}
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]
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},
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{
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'params': {
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'algo': 'sentiment-taiger',
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'intype': 'direct',
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'expanded-jsonld': 0,
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'informat': 'text',
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'prefix': '',
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'plugin_type': 'analysisPlugin',
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'urischeme': 'RFC5147String',
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'outformat': 'json-ld',
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'conversion': 'full',
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'language': 'en',
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'apikey': '00000',
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'algorithm': 'sentiment-taiger'
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},
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'input': 'The pillow is in the wardrobe',
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'expected': {
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'sentiments': [
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{'marl:hasPolarity': 'marl:Neutral'}],
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},
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'responses': [
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{
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'url': TAIGER_ENDPOINT,
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'json': {
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"inputText": "The pillow is in the wardrobe",
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"normalizedText": "The pillow is in the wardrobe",
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"positivityScore": -2.723999097522657,
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"positivityCategory": "neu"
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}
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}
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]
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}
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]
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if __name__ == '__main__':
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from senpy import easy_test
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easy_test()
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