def tokenize(self,
                 sentence,
                 normalize=True,
                 is_feature=False,
                 is_surface=False,
                 return_list=False,
                 func_normalizer=text_preprocess.normalize_text):
        # type: (text_preprocess, bool, bool, bool, bool, Callable[[str], text_type])->Union[List[text_type], TokenizedSenetence]
        """This method returns tokenized result.
        If return_list==True(default), this method returns list whose element is tuple consisted with word_stem and POS.
        If return_list==False, this method returns TokenizedSenetence object.
        """
        assert isinstance(normalize, bool)
        assert isinstance(sentence, text_type)
        normalized_sentence = func_normalizer(sentence)
        result = self.call_juman_interface(normalized_sentence)

        token_objects = [
            self.__extract_morphological_information(
                mrph_object=morph_object,
                is_surface=is_surface,
                is_feature=is_feature
            )
            for morph_object in result]

        if return_list:
            tokenized_objects = TokenizedSenetence(
                sentence=sentence,
                tokenized_objects=token_objects
            )
            return tokenized_objects.convert_list_object()
        else:
            tokenized_objects = TokenizedSenetence(
                sentence=sentence,
                tokenized_objects=token_objects)

            return tokenized_objects
This method returns tokenized result.
        If return_list==True(default), this method returns list whose element is tuple consisted with word_stem and POS.
        If return_list==False, this method returns TokenizedSenetence object.