code: def _create_sentence_objects(self):
          
          sentence_objects = []
          sentences = sent_tokenize(self.raw, tokenizer=self.tokenizer)
          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. This only works if the sentence splitter
              # does not perform any character replacements or changes to
              # white space.
              # Working: NLTKPunktTokenizer
              # Not working: PatternTokenizer
              try:
                  start_index = self.raw.index(sent, char_index)
                  char_index += len(sent)
                  end_index = start_index + len(sent)
              except ValueError:
                  start_index = None
                  end_index = None
              # 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
docs: Returns a list of Sentence objects from the raw text.