code: def _create_sentence_objects(self):
      '''Returns a list of Sentence objects from the raw text.
      '''
      sentence_objects = []
      sent_tokenizer = SentenceTokenizer(locale=self.language.code)
      seq = Sequence(self.raw)
      seq = sent_tokenizer.transform(seq)
      for start_index, end_index in zip(seq.idx[:-1], seq.idx[1:]):
        # Sentences share the same models as their parent blob
        sent = seq.text[start_index: end_index].strip()
        if not sent: continue
        s = Sentence(sent, start_index=start_index, end_index=end_index)
        s.detected_languages = self.detected_languages
        sentence_objects.append(s)
      return sentence_objectf _create_sentence_objects(self):
      '''Returns a list of Sentence objects from the raw text.
      '''
      sentence_objects = []
      sent_tokenizer = SentenceTokenizer(locale=self.language.code)
      seq = Sequence(self.raw)
      seq = sent_tokenizer.transform(seq)
      for start_index, end_index in zip(seq.idx[:-1], seq.idx[1:]):
        # Sentences share the same models as their parent blob
        sent = seq.text[start_index: end_index].strip()
        if not sent: continue
        s = Sentence(sent, start_index=start_index, end_index=end_index)
        s.detected_languages = self.detected_languages
        sentence_objects.append(s)
      return sentence_objects
docs: Returns a list of Sentence objects from the raw text.