{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Senpy in 10 minutes\n", "\n", "This tutorial assumes you have completed the [1 minute tutorial](Quickstart-1minute.ipynb) and you know how to access the API.\n", "\n", "It covers:\n", "\n", "* Annotating entiment with a sentiment analysis service\n", "* Annotating emotions\n", "* Interoperability of services\n", "* Using other semantic formats (RDF)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Requirements" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once again, we will use the demo server at http://senpy.gsi.upm.es.\n", "This time, we will use the requests library.\n", "\n", "We will use a variable for our endpoint, so you can try this examples on a different senpy instance:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "endpoint = 'http://senpy.gsi.upm.es/api'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We will also add a function to get syntax highlighting for the JSON-LD/Turtle results:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "try:\n", " from IPython.display import Code\n", " def pretty(txt, language='json-ld'):\n", " return Code(txt, language=language)\n", "except ImportError:\n", " def pretty(txt, **kwargs):\n", " print(txt)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Sentiment Analysis of Text" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To start, let us analyse the sentiment in the following sentence: *senpy is awesome*.\n", "\n", "For now, we will use the [sentiment140](http://www.sentiment140.com/) service, through the sentiment140 plugin.\n", "We will later cover how to use a different service.\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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       "  "@type": "Results",\n",
       "  "entries": [\n",
       "    {\n",
       "      "@id": "prefix:",\n",
       "      "@type": "Entry",\n",
       "      "marl:hasOpinion": [\n",
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       "          "marl:hasPolarity": "marl:Positive",\n",
       "          "prov:wasGeneratedBy": "prefix:Analysis_1554391718.7649393"\n",
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       "      "nif:isString": "Senpy is awesome",\n",
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       "    "http://www.gsi.upm.es/onto/senpy/ns#Results"\n",
       "  ],\n",
       "  "http://www.w3.org/ns/prov#used": [\n",
       "    {\n",
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       "      "@type": [\n",
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       "      ],\n",
       "      "http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#isString": [\n",
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       "          "@value": "Senpy is awesome"\n",
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       "      "http://www.gsi.dit.upm.es/ontologies/marl/ns#hasOpinion": [\n",
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       "              "@value": "marl:Positive"\n",
       "            }\n",
       "          ],\n",
       "          "http://www.w3.org/ns/prov#wasGeneratedBy": [\n",
       "            {\n",
       "              "@id": "http://senpy.invalid/Analysis_1554389672.269198"\n",
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       "      ],\n",
       "      "http://www.gsi.dit.upm.es/ontologies/onyx/ns#hasEmotionSet": []\n",
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\n" ], "text/latex": [ "\\begin{Verbatim}[commandchars=\\\\\\{\\}]\n", "\\PY{p}{\\PYZob{}}\n", " \\PY{n+nd}{\\PYZdq{}@context\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}http://senpy.gsi.upm.es/api/contexts/YXBpL3NlbnRpbWVudC1iYXNpYz9pbnB1dD1TZW5weStpcythd2Vzb21lIw\\PYZpc{}3D\\PYZpc{}3D\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nd}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Results\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nt}{\\PYZdq{}entries\\PYZdq{}}\\PY{p}{:} \\PY{p}{[}\n", " \\PY{p}{\\PYZob{}}\n", " \\PY{n+nd}{\\PYZdq{}@id\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}prefix:\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nd}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Entry\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nt}{\\PYZdq{}marl:hasOpinion\\PYZdq{}}\\PY{p}{:} \\PY{p}{[}\n", " \\PY{p}{\\PYZob{}}\n", " \\PY{n+nd}{\\PYZdq{}@type\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Sentiment\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nt}{\\PYZdq{}marl:hasPolarity\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}marl:Neutral\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nt}{\\PYZdq{}prov:wasGeneratedBy\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}prefix:Analysis\\PYZus{}1554389675.9911203\\PYZdq{}}\n", " \\PY{p}{\\PYZcb{}}\n", " \\PY{p}{]}\\PY{p}{,}\n", " \\PY{n+nt}{\\PYZdq{}nif:isString\\PYZdq{}}\\PY{p}{:} \\PY{l+s+s2}{\\PYZdq{}Senpy is awesome\\PYZdq{}}\\PY{p}{,}\n", " \\PY{n+nt}{\\PYZdq{}onyx:hasEmotionSet\\PYZdq{}}\\PY{p}{:} \\PY{p}{[}\\PY{p}{]}\n", " \\PY{p}{\\PYZcb{}}\n", " \\PY{p}{]}\n", "\\PY{p}{\\PYZcb{}}\n", "\\end{Verbatim}\n" ], "text/plain": [ "{\n", " \"@context\": \"http://senpy.gsi.upm.es/api/contexts/YXBpL3NlbnRpbWVudC1iYXNpYz9pbnB1dD1TZW5weStpcythd2Vzb21lIw%3D%3D\",\n", " \"@type\": \"Results\",\n", " \"entries\": [\n", " {\n", " \"@id\": \"prefix:\",\n", " \"@type\": \"Entry\",\n", " \"marl:hasOpinion\": [\n", " {\n", " \"@type\": \"Sentiment\",\n", " \"marl:hasPolarity\": \"marl:Neutral\",\n", " \"prov:wasGeneratedBy\": \"prefix:Analysis_1554389675.9911203\"\n", " }\n", " ],\n", " \"nif:isString\": \"Senpy is awesome\",\n", " \"onyx:hasEmotionSet\": []\n", " }\n", " ]\n", "}" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import requests\n", "res = requests.get(f'{endpoint}/sentiment-basic',\n", " params={\"input\": \"Senpy is awesome\"})\n", "pretty(res.text)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you can see, the structure and annotation schema of the response is the same.\n", "This makes it very easy to compare and migrate to different services.\n", "\n", "Service interoperability is not only useful for users.\n", "It is also key for other features such as [automated evaluation](#Evaluation).\n", "This is a compelling reason to adapt existing services to use the Senpy API.\n", "In fact, the `sentiment140` senpy service is proxy to the public [Sentiment 140 service](http://www.sentiment140.com/)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Emotion analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "Senpy uses the `onyx` vocabulary to represent emotions, which incorporates the notion of `EmotionSet`'s, an emotion that is composed of several emotions.\n", "In a nutshell, an `Entry` is linked to one or more `EmotionSet`, which in turn is made up of one or more `Emotion`.\n", "\n", "Let's illustrate it with an example, using the `emotion-depechemood` plugin." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
{\n",
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       "            },\n",
       "            {\n",
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\"onyx:hasEmotionCategory\": \"wna:indifference\",\n", " \"onyx:hasEmotionIntensity\": 0.1374081151031531\n", " },\n", " {\n", " \"@type\": \"Emotion\",\n", " \"onyx:hasEmotionCategory\": \"wna:joy\",\n", " \"onyx:hasEmotionIntensity\": 0.12267040802346799\n", " },\n", " {\n", " \"@type\": \"Emotion\",\n", " \"onyx:hasEmotionCategory\": \"wna:awe\",\n", " \"onyx:hasEmotionIntensity\": 0.21085262130713067\n", " },\n", " {\n", " \"@type\": \"Emotion\",\n", " \"onyx:hasEmotionCategory\": \"wna:sadness\",\n", " \"onyx:hasEmotionIntensity\": 0.09950234435617733\n", " }\n", " ],\n", " \"prov:wasGeneratedBy\": \"prefix:Analysis_1554389679.0535374\"\n", " }\n", " ]\n", " }\n", " ]\n", "}" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "res = requests.get(f'{endpoint}/emotion-depechemood',\n", " params={\"input\": \"Senpy is a wonderful that service\"})\n", "pretty(res.text)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you have probably noticed, there are several emotions in this result, each with a different intensity.\n", "\n", "We can also tell senpy to only return the emotion with the maximum intensity using the `maxemotion` parameter:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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@prefix : <http://www.gsi.upm.es/onto/senpy/ns#> .\n",
       "@prefix dc: <http://dublincore.org/2012/06/14/dcelements#> .\n",
       "@prefix emoml: <http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/emotionml/ns#> .\n",
       "@prefix endpoint: <http://senpy.gsi.upm.es/api/> .\n",
       "@prefix fam: <http://vocab.fusepool.info/fam#> .\n",
       "@prefix marl: <http://www.gsi.dit.upm.es/ontologies/marl/ns#> .\n",
       "@prefix nif: <http://persistence.uni-leipzig.org/nlp2rdf/ontologies/nif-core#> .\n",
       "@prefix onyx: <http://www.gsi.dit.upm.es/ontologies/onyx/ns#> .\n",
       "@prefix prefix: <http://senpy.invalid/> .\n",
       "@prefix prov: <http://www.w3.org/ns/prov#> .\n",
       "@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .\n",
       "@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .\n",
       "@prefix senpy: <http://www.gsi.upm.es/onto/senpy/ns#> .\n",
       "@prefix wna: <http://www.gsi.dit.upm.es/ontologies/wnaffect/ns#> .\n",
       "@prefix xml: <http://www.w3.org/XML/1998/namespace> .\n",
       "@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .\n",
       "\n",
       "prefix: a senpy:Entry ;\n",
       "    nif:isString "Senpy is the best framework for semantic sentiment analysis, and very easy to use" ;\n",
       "    marl:hasOpinion [ a senpy:Sentiment ;\n",
       "            marl:hasPolarity "marl:Positive" ;\n",
       "            prov:wasGeneratedBy prefix:Analysis_1554389682.350598 ] .\n",
       "\n",
       "[] a senpy:Results ;\n",
       "    prov:used prefix: .\n",
       "
\n" ], "text/latex": [ "\\begin{Verbatim}[commandchars=\\\\\\{\\}]\n", "\\PY{k}{@prefix}\\PY{+w}{ }\\PY{n+nn}{:}\\PY{+w}{ }\\PY{n+nv}{\\PYZlt{}http://www.gsi.upm.es/onto/senpy/ns\\PYZsh{}\\PYZgt{}}\\PY{+w}{ }\\PY{p}{.}\n", "\\PY{k}{@prefix}\\PY{+w}{ }\\PY{n+nn}{dc:}\\PY{+w}{ }\\PY{n+nv}{\\PYZlt{}http://dublincore.org/2012/06/14/dcelements\\PYZsh{}\\PYZgt{}}\\PY{+w}{ }\\PY{p}{.}\n", "\\PY{k}{@prefix}\\PY{+w}{ }\\PY{n+nn}{emoml:}\\PY{+w}{ }\\PY{n+nv}{\\PYZlt{}http://www.gsi.dit.upm.es/ontologies/onyx/vocabularies/emotionml/ns\\PYZsh{}\\PYZgt{}}\\PY{+w}{ }\\PY{p}{.}\n", "\\PY{k}{@prefix}\\PY{+w}{ }\\PY{n+nn}{endpoint:}\\PY{+w}{ }\\PY{n+nv}{\\PYZlt{}http://senpy.gsi.upm.es/api/\\PYZgt{}}\\PY{+w}{ }\\PY{p}{.}\n", "\\PY{k}{@prefix}\\PY{+w}{ }\\PY{n+nn}{fam:}\\PY{+w}{ }\\PY{n+nv}{\\PYZlt{}http://vocab.fusepool.info/fam\\PYZsh{}\\PYZgt{}}\\PY{+w}{ }\\PY{p}{.}\n", "\\PY{k}{@prefix}\\PY{+w}{ }\\PY{n+nn}{marl:}\\PY{+w}{ 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"text/plain": [ "@prefix : .\n", "@prefix dc: .\n", "@prefix emoml: .\n", "@prefix endpoint: .\n", "@prefix fam: .\n", "@prefix marl: .\n", "@prefix nif: .\n", "@prefix onyx: .\n", "@prefix prefix: .\n", "@prefix prov: .\n", "@prefix rdf: .\n", "@prefix rdfs: .\n", "@prefix senpy: .\n", "@prefix wna: .\n", "@prefix xml: .\n", "@prefix xsd: .\n", "\n", "prefix: a senpy:Entry ;\n", " nif:isString \"Senpy is the best framework for semantic sentiment analysis, and very easy to use\" ;\n", " marl:hasOpinion [ a senpy:Sentiment ;\n", " marl:hasPolarity \"marl:Positive\" ;\n", " prov:wasGeneratedBy prefix:Analysis_1554389682.350598 ] .\n", "\n", "[] a senpy:Results ;\n", " prov:used prefix: .\n" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "res = requests.get(f'{endpoint}/sentiment140',\n", " params={\"input\": \"Senpy is the best framework for semantic sentiment analysis, and very easy to use\",\n", " \"outformat\": \"turtle\"})\n", 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