def _create_sentence_objects(self):
'''Returns a list of Sentence objects from the raw text.
'''
sentence_objects = []
sentences = sent_tokenize(self.raw)
char_index = 0 # Keeps track of character index within the blob
for sent in sentences:
# Compute the start and end indices of the sentence
# within the blob
start_index = self.raw.index(sent, char_index)
char_index += len(sent)
end_index = start_index + len(sent)
# Sentences share the same models as their parent blob
s = Sentence(sent, start_index=start_index, end_index=end_index,
tokenizer=self.tokenizer, np_extractor=self.np_extractor,
pos_tagger=self.pos_tagger, analyzer=self.analyzer,
parser=self.parser, classifier=self.classifier)
sentence_objects.append(s)
return sentence_objects
def _create_sentence_objects(self):
'''Returns a list of Sentence objects from the raw text.
'''
sentence_objects = []
sentences = sent_tokenize(self.raw)
char_index = 0 # Keeps track of character index within the blob
for sent in sentences:
# Compute the start and end indices of the sentence
# within the blob
start_index = self.raw.index(sent, char_index)
char_index += len(sent)
end_index = start_index + len(sent)
# Sentences share the same models as their parent blob
s = Sentence(sent, start_index=start_index, end_index=end_index,
tokenizer=self.tokenizer, np_extractor=self.np_extractor,
pos_tagger=self.pos_tagger, analyzer=self.analyzer,
parser=self.parser, classifier=self.classifier)
sentence_objects.append(s)
return sentence_objects
def test_sent_tokenize(self):
tokens = sent_tokenize(self.text)
assert_true(is_generator(tokens)) # It's a generator
assert_equal(list(tokens), self.tokenizer.tokenize(self.text))
def test_sent_tokenize(self):
tokens = sent_tokenize(self.text)
assert_true(is_generator(tokens)) # It's a generator
assert_equal(list(tokens), self.tokenizer.tokenize(self.text))
