mirror of
https://github.com/gsi-upm/senpy
synced 2024-11-22 16:12:29 +00:00
70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
#!/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 self.pos_synset.has_key((synset.pos(), synset.offset())):
|
|
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 |