def trained_tagger(existing=False):
#returns a trained trigram tagger
if existing:
trigram_tagger = pickle.load(open('trained_tagger.pkl', 'rb'))
return trigram_tagger
# Aggregate trained sentences for N-Gram Taggers
train_sents = nltk.corpus.brown.tagged_sents()
train_sents += nltk.corpus.conll2000.tagged_sents()
train_sents += nltk.corpus.treebank.tagged_sents()
# Create instance of SubjectTrigramTagger and persist instance of it
trigram_tagger = SubjectTrigramTagger(train_sents)
pickle.dump(trigram_tagger, open('trained_tagger.pkl', 'wb'))
return trigram_tagger
def trained_tagger(existing=False):
"""Returns a trained trigram tagger
existing : set to True if already trained tagger has been pickled
"""
if existing:
trigram_tagger = pickle.load(
open('./subject_extraction/trained_tagger.pkl', 'rb'))
return trigram_tagger
# Aggregate trained sentences for N-Gram Taggers
train_sents = nltk.corpus.brown.tagged_sents()
train_sents += nltk.corpus.conll2000.tagged_sents()
train_sents += nltk.corpus.treebank.tagged_sents()
# Create instance of SubjectTrigramTagger and persist instance of it
trigram_tagger = SubjectTrigramTagger(train_sents)
pickle.dump(trigram_tagger,
open('./subject_extraction/trained_tagger.pkl', 'wb'))
return trigram_tagger