Commit 400e8fba authored by J. Fernando Sánchez's avatar J. Fernando Sánchez
Browse files

Taiger

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# Senpy Plugin Taiger
Service that analyzes sentiments from social posts written in Spanish or English.
## Usage
To use this plugin, you should use a GET Requests with the following possible params:
Params:
- Input: text to analyse.(required)
- Endpoint: Enpoint to the Taiger service.
## Example of Usage
Example request:
```
http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-taiger&inputText=This%20is%20amazing
```
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.
For example, this would be the example respond for the request done.
```
{
"@context": "http://localhost:5005/api/contexts/Results.jsonld",
"@id": "_:Results_1532449339.5887764",
"@type": "results",
"analysis": [
"endpoint:plugins/sentiment-taiger_0.1"
],
"entries": [
{
"@id": "#",
"@type": "entry",
"emotions": [],
"entities": [],
"nif:isString": "This is amazing",
"sentiments": [
{
"@id": "Opinion0",
"@type": "sentiment",
"marl:hasPolarity": "marl:Positive",
"marl:polarityValue": -1.4646806570973374,
"normalizedText": "This is amazing",
"prov:wasGeneratedBy": "endpoint:plugins/sentiment-taiger_0.1"
}
],
"suggestions": [],
"topics": []
}
]
}
```
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`.
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"
version: '3'
services:
dev:
image: gsiupm/senpy:latest
working_dir: "/senpy-plugins"
ports:
- "127.0.0.1:5005:5000"
volumes:
- ".:/senpy-plugins"
environment:
TAIGER_ENDPOINT: 'http://34.244.91.7:8080/sentiment/classifyPositivity'
# -*- 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
TAIGER_ENDPOINT = os.environ.get("TAIGER_ENDPOINT", 'http://134.244.91.7:8080/sentiment/classifyPositivity')
class TaigerPlugin(SentimentPlugin):
'''
Service that analyzes sentiments from social posts written in Spanish or English.
Example request:
http://senpy.cluster.gsi.dit.upm.es/api/?algo=sentiment-taiger&inputText=This%20is%20amazing
'''
name = 'sentiment-taiger'
author = 'GSI UPM'
version = "0.1"
maxPolarityValue = 0
minPolarityValue = -10
def _polarity(self, value):
if 'neu' in value:
polarity = 'marl:Neutral'
elif 'neg' in value:
polarity = 'marl:Negative'
elif 'pos' in value:
polarity = 'marl:Positive'
return polarity
def analyse_entry(self, entry, params):
txt = entry['nif:isString']
api = TAIGER_ENDPOINT
parameters = {
'inputText': txt
}
try:
r = requests.get(
api, params=parameters, timeout=3)
api_response = r.json()
except requests.exceptions.Timeout:
raise Error("No response from the API")
except Exception as ex:
raise Error("There was a problem with the endpoint: {}".format(ex))
if not api_response.get('positivityCategory'):
raise Error('No positive category in response: {}'.format(r.json()))
self.log.debug(api_response)
agg_polarity = self._polarity(api_response.get('positivityCategory'))
normalized_text = api_response.get('normalizedText', None)
agg_opinion = Sentiment(
id="Opinion0",
marl__hasPolarity=agg_polarity,
marl__polarityValue=api_response['positivityScore']
)
agg_opinion["normalizedText"] = api_response['normalizedText']
agg_opinion.prov(self)
entry.sentiments.append(agg_opinion)
yield entry
test_cases = [
{
'params': {
'algo': 'sentiment-taiger',
'intype': 'direct',
'expanded-jsonld': 0,
'informat': 'text',
'prefix': '',
'plugin_type': 'analysisPlugin',
'urischeme': 'RFC5147String',
'outformat': 'json-ld',
'conversion': 'full',
'language': 'en',
'apikey': '00000',
'algorithm': 'sentiment-taiger'
},
'input': 'I hate to say this',
'expected': {
'sentiments': [
{'marl:hasPolarity': 'marl:Negative'}],
},
'responses': [
{
'url': TAIGER_ENDPOINT,
'json': {
"inputText": "I hate to say this",
"normalizedText": "I hate to say this",
"positivityScore": -1.8951251587831475,
"positivityCategory": "neg"
}
}
]
},
{
'params': {
'algo': 'sentiment-taiger',
'intype': 'direct',
'expanded-jsonld': 0,
'informat': 'text',
'prefix': '',
'plugin_type': 'analysisPlugin',
'urischeme': 'RFC5147String',
'outformat': 'json-ld',
'conversion': 'full',
'language': 'en',
'apikey': '00000',
'algorithm': 'sentiment-taiger'
},
'input': 'This is amazing',
'expected': {
'sentiments': [
{'marl:hasPolarity': 'marl:Positive'}],
},
'responses': [
{
'url': TAIGER_ENDPOINT,
'json': {
"inputText": "This is amazing ",
"normalizedText": "This is amazing",
"positivityScore": -1.4646806570973374,
"positivityCategory": "pos"
}
}
]
},
{
'params': {
'algo': 'sentiment-taiger',
'intype': 'direct',
'expanded-jsonld': 0,
'informat': 'text',
'prefix': '',
'plugin_type': 'analysisPlugin',
'urischeme': 'RFC5147String',
'outformat': 'json-ld',
'conversion': 'full',
'language': 'en',
'apikey': '00000',
'algorithm': 'sentiment-taiger'
},
'input': 'The pillow is in the wardrobe',
'expected': {
'sentiments': [
{'marl:hasPolarity': 'marl:Neutral'}],
},
'responses': [
{
'url': TAIGER_ENDPOINT,
'json': {
"inputText": "The pillow is in the wardrobe",
"normalizedText": "The pillow is in the wardrobe",
"positivityScore": -2.723999097522657,
"positivityCategory": "neu"
}
}
]
}
]
if __name__ == '__main__':
from senpy import easy_test
easy_test()
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