mirror of
https://github.com/gsi-upm/senpy
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248 lines
9.2 KiB
Python
248 lines
9.2 KiB
Python
# -*- 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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from senpy.utils import check_template
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class MeaningCloudPlugin(SentimentPlugin):
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'''
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Sentiment analysis with meaningCloud service.
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To use this plugin, you need to obtain an API key from meaningCloud signing up here:
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https://www.meaningcloud.com/developer/login
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When you had obtained the meaningCloud API Key, you have to provide it to the plugin, using param apiKey.
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Example request:
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http://senpy.cluster.gsi.dit.upm.es/api/?algo=meaningCloud&language=en&apiKey=<API key>&input=I%20love%20Madrid.
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'''
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name = 'sentiment-meaningcloud'
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author = 'GSI UPM'
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version = "1.1"
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maxPolarityValue = 1
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minPolarityValue = -1
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extra_params = {
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"language": {
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"aliases": ["language", "l"],
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"required": True,
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"options": ["en","es","ca","it","pt","fr","auto"],
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"default": "auto"
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},
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"apikey":{
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"aliases": ["apiKey", "meaningcloud-key", "meaningcloud-apikey"],
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"required": True
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}
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}
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def _polarity(self, value):
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if 'NONE' in value:
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polarity = 'marl:Neutral'
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polarityValue = 0
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elif 'N' in value:
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polarity = 'marl:Negative'
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polarityValue = -1
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elif 'P' in value:
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polarity = 'marl:Positive'
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polarityValue = 1
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return polarity, polarityValue
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def analyse_entry(self, entry, params):
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txt = entry['nif:isString']
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api = 'http://api.meaningcloud.com/'
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lang = params.get("language")
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model = "general"
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key = params["apikey"]
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parameters = {
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'key': key,
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'model': model,
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'lang': lang,
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'of': 'json',
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'txt': txt,
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'tt': 'a'
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}
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try:
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r = requests.post(
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api + "sentiment-2.1", params=parameters, timeout=3)
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parameters['lang'] = r.json()['model'].split('_')[1]
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lang = parameters['lang']
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r2 = requests.post(
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api + "topics-2.0", params=parameters, timeout=3)
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except requests.exceptions.Timeout:
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raise Error("Meaning Cloud API does not response")
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api_response = r.json()
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api_response_topics = r2.json()
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if not api_response.get('score_tag'):
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raise Error(r.json())
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entry['language_detected'] = lang
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self.log.debug(api_response)
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agg_polarity, agg_polarityValue = self._polarity(
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api_response.get('score_tag', 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=agg_polarityValue,
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marl__opinionCount=len(api_response['sentence_list']))
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agg_opinion.prov(self)
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entry.sentiments.append(agg_opinion)
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self.log.debug(api_response['sentence_list'])
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count = 1
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for sentence in api_response['sentence_list']:
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for nopinion in sentence['segment_list']:
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self.log.debug(nopinion)
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polarity, polarityValue = self._polarity(
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nopinion.get('score_tag', None))
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opinion = Sentiment(
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id="Opinion{}".format(count),
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marl__hasPolarity=polarity,
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marl__polarityValue=polarityValue,
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marl__aggregatesOpinion=agg_opinion.get('id'),
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nif__anchorOf=nopinion.get('text', None),
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nif__beginIndex=int(nopinion.get('inip', None)),
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nif__endIndex=int(nopinion.get('endp', None)))
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count += 1
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opinion.prov(self)
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entry.sentiments.append(opinion)
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mapper = {'es': 'es.', 'en': '', 'ca': 'es.', 'it':'it.', 'fr':'fr.', 'pt':'pt.'}
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for sent_entity in api_response_topics['entity_list']:
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resource = "_".join(sent_entity.get('form', None).split())
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entity = Entity(
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id="Entity{}".format(sent_entity.get('id')),
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itsrdf__taIdentRef="http://{}dbpedia.org/resource/{}".format(
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mapper[lang], resource),
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nif__anchorOf=sent_entity.get('form', None),
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nif__beginIndex=int(sent_entity['variant_list'][0].get('inip', None)),
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nif__endIndex=int(sent_entity['variant_list'][0].get('endp', None)))
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sementity = sent_entity['sementity'].get('type', None).split(">")[-1]
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entity['@type'] = "ODENTITY_{}".format(sementity)
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entity.prov(self)
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entry.entities.append(entity)
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for topic in api_response_topics['concept_list']:
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if 'semtheme_list' in topic:
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for theme in topic['semtheme_list']:
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concept = Topic()
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concept.id = "Topic{}".format(topic.get('id'))
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concept['@type'] = "ODTHEME_{}".format(theme['type'].split(">")[-1])
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concept['fam:topic-reference'] = "http://dbpedia.org/resource/{}".format(theme['type'].split('>')[-1])
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entry.prov(self)
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entry.topics.append(concept)
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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-meaningCloud',
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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-meaningCloud'
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},
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'input': 'Hello World Obama',
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'expected': {
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'sentiments': [
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{'marl:hasPolarity': 'marl:Neutral'}],
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'entities': [
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{'itsrdf:taIdentRef': 'http://dbpedia.org/resource/Obama'}],
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'topics': [
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{'fam:topic-reference': 'http://dbpedia.org/resource/Astronomy'}]
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},
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'responses': [
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{
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'url': 'http://api.meaningcloud.com/sentiment-2.1',
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'method': 'POST',
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'json': {
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'model': 'general_en',
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'sentence_list': [{
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'text':
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'Hello World',
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'endp':
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'10',
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'inip':
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'0',
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'segment_list': [{
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'text':
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'Hello World',
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'segment_type':
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'secondary',
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'confidence':
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'100',
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'inip':
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'0',
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'agreement':
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'AGREEMENT',
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'endp':
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'10',
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'polarity_term_list': [],
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'score_tag':
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'NONE'
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}],
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'score_tag':
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'NONE',
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}],
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'score_tag':
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'NONE'
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}
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}, {
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'url': 'http://api.meaningcloud.com/topics-2.0',
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'method': 'POST',
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'json': {
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'entity_list': [{
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'form':
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'Obama',
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'id':
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'__1265958475430276310',
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'variant_list': [{
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'endp': '16',
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'form': 'Obama',
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'inip': '12'
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}],
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'sementity': {
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'fiction': 'nonfiction',
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'confidence': 'uncertain',
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'class': 'instance',
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'type': 'Top>Person'
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}
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}],
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'concept_list': [{
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'form':
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'world',
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'id':
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'5c053cd39d',
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'relevance':
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'100',
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'semtheme_list': [{
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'id': 'ODTHEME_ASTRONOMY',
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'type': 'Top>NaturalSciences>Astronomy'
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}]
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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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