def get_model(cls, aug_src, lang, dict_path, force_reload):
if aug_src == 'wordnet':
return nmw.WordNet(lang=lang, is_synonym=True)
elif aug_src == 'ppdb':
return init_ppdb_model(dict_path=dict_path, force_reload=force_reload)
raise ValueError('aug_src is not one of `wordnet` or `ppdb` while {} is passed.'.format(aug_src))
def get_random_words_synonyms(original_words):
"""
Helper for RI: picks a random word in 'original_words' which is not a stopword. Returns a list of its synonyms (and the word).
"""
model = nmw.WordNet(lang='eng', is_synonym=True)
filtered_words = [w for w in original_words
if w not in english_stopwords] # remove stopwords
while True:
candidate_word = random.choice(filtered_words)
# print("Candidate:", candidate_word)
candidate_syns = model.predict(candidate_word)
# print("Before:", candidate_syns)
if candidate_word in candidate_syns: # remove all occurrences of candidate_word in candidate_syns
candidate_syns = list(
filter(lambda a: a != candidate_word, candidate_syns))
# print("After:", candidate_syns)
if candidate_syns: # return, if not empty
return candidate_syns, candidate_word
def get_model(cls, aug_src, lang):
if aug_src == 'wordnet':
return nmw.WordNet(lang=lang, is_synonym=False)
def get_model(cls, lang, is_synonym):
return nmw.WordNet(lang=lang, is_synonym=is_synonym)
