def contain_verb(tag, verb):
'''whether a sentence contain 'verb' tagged with 'VB'
'''
for word, pos in tag:
if (pos.startswith('VB') and
util.lemmatize(word, 'v')==verb):
return True
return False
def contain_query_words(sentence, query, query_pos='v'):
# has to compare each query word to the base form of the
# words in the sentence, which might be time consuming
if query:
keywords = query.split()
for keyword in keywords:
sentence = [util.lemmatize(word, query_pos) for word
in sentence]
if keyword not in sentence:
return False
return True
def canonical_tagged_sentence(tokens, tags):
keep = []
for token, tag in zip(tokens, tags):
if tag in ['DT', 'PRP$', 'TO', '.', '$', ':', ',',
'POS', '``', "''", 'CD']:
continue
token = util.lemmatize(token, util.tag2wnpos(tag))
if tag == 'IN':
token = 'IN'
elif token == "n't":
token = 'not'
elif token == "'s" and tag.startswith('VB'):
token = 'be'
elif token == "'re":
token = 'be'
keep.append(token)
# use str is because pytable doesn't support unicode
# in case we want to store it to pytable
return str(' '.join(keep))
