def noun_subjectivity(noun):
import src.im2text.data as data
subjclues = data.subjectivity_clues()
entry = subjclues.get((lemmatize(noun, wn.NOUN), 'noun'), None)
if entry:
return 'strong' if entry.type.startswith('strong') else 'weak'
else:
return None
def verb_subjectivity(verb, synonym_threshold=3):
import src.im2text.data as data
subjclues = data.subjectivity_clues()
entry = subjclues.get((lemmatize(verb, wn.VERB), 'verb'), None)
if entry is not None:
return 'strong' if entry['type'].startswith('strong') else 'weak'
entries = [subjclues.get((synonym, 'verb'), None)
for synonym in synonyms(verb)]
subjs = [None if not entry else entry['type'] for entry in entries]
# at least 2 synonyms are in subj lexicon, then we consider the word as subjective
if len(filter(lambda e: e is not None, subjs)) >= synonym_threshold:
if any(itertools.imap(lambda s: s and s.startswith('strong'), subjs)):
return 'strong'
elif any(itertools.imap(lambda s: s and s.startswith('weak'), subjs)):
return 'weak'
return None
def get_subjclue(word, pos):
def word_type(pos):
if pos.startswith('VB'):
return 'verb'
elif pos.startswith('NN'):
return 'noun'
elif pos.startswith('JJ'):
return 'adj'
elif pos.startswith('RB'):
return 'adverb'
else:
return 'other'
import src.im2text.data as data
subjclues = data.subjectivity_clues()
lemma = lemmatize(word, pos)
entry = subjclues.get((lemma, word_type(pos)), None)
if entry:
return entry
else:
entry = subjclues.get((lemma, 'anypos'), None)
return entry