def __init__(self, document: str, kuzure_flag=False, do_segment=False): """ Args: document (str): 解析対象文. sentence_class (bool, optional): 崩れ文かどうか. Defaults to False. do_segment (bool, optional): 文区切りをするかどうか. Defaults to False. """ super().__init__() self.document = document self.sentence_class = get_sentence_class(kuzure_flag) self.do_segment = do_segment if type(self.document) == list: self.do_segment = False request_json = {'document': self.document, 'type': self.sentence_class, 'do_segment': self.do_segment} response_dict = self.get_response_dict( relative_url='nlp/beta/user_attribute', request_body=request_json) self.message = response_dict['message'] self.user_attribute_result = UserAttributeResult( response_dict['result']) self.status = response_dict['status']
def __init__(self, sentence: str, kuzure_flag=False, dic_class=[]): """ Args: sentence (str): 解析対象文. sentence_class (bool, optional): 崩れ文かどうか. Defaults to False. dic_class (list, optional): 専門用語辞書. Defaults to []. Raises: ParseError: dic_classにエラーがある場合. """ super().__init__() self.sentence = sentence self.sentence_class = get_sentence_class(kuzure_flag) if check_dic_class(dic_class): self.dic_class = dic_class else: raise ParseError('dic_classにエラーがあります.') request_json = { 'sentence': self.sentence, 'type': self.sentence_class, 'dic_type': self.dic_class } response_dict = self.get_response_dict(relative_url='nlp/v1/parse', request_body=request_json) self.message = response_dict['message'] self.status = response_dict['status'] self.parse_result_list = [] for result_dict in response_dict['result']: self.parse_result_list.append(ParseResult(result_dict))
def __init__(self, s1: str, s2: str, kuzure_flag=False, dic_class=[]): """ Args: s1 (str): 解析対象文1. s2 (str): 解析対象文2. kuzure_flag (bool, optional): 崩れ文かどうか. Defaults to False. dic_class (list, optional): 専門用語辞書. Defaults to []. Raises: SimilarityError: dic_classにエラーがあります. """ super().__init__() self.s1 = s1 self.s2 = s2 self.sentence_class = get_sentence_class(kuzure_flag) if check_dic_class(dic_class): self.dic_class = dic_class else: raise SimilarityError('dic_classにエラーがあります.') request_json = {'s1': self.s1, 's2': self.s2, 'type': self.sentence_class, 'dic_type': self.dic_class} response_dict = self.get_response_dict( relative_url='nlp/v1/similarity', request_body=request_json) self.message = response_dict['message'] self.status = response_dict['status'] self.similarity_result = SimilarityResult(response_dict['result'])
def __init__(self, document: str, kuzure_flag=False, do_segment=False, max_keyword_num=5, dic_class=[]): """ Args: document (str): 解析対象文. sentence_class (str, optional): 崩れ文かどうか. Defaults to 'default'. do_segment (bool, optional): 文区切りするかどうか. Defaults to False. max_keyword_num (int, optional): 抽出する単語上限. Defaults to 5. dic_class (list, optional): 専門用語辞書. Defaults to []. Raises: KeywordError: dic_classにエラーがある場合. """ super().__init__() self.document = document self.sentence_class = get_sentence_class(kuzure_flag) self.do_segment = do_segment if type(self.document) == list: self.do_segment = False if max_keyword_num >= 1: self.max_keyword_num = max_keyword_num else: self.max_keyword_num = 5 if check_dic_class(dic_class): self.dic_class = dic_class else: raise KeywordError('dic_classにエラーがあります.') request_json = {'document': self.document, 'type': self.sentence_class, 'do_segment': self.do_segment, 'max_keyword_num': self.max_keyword_num, 'dic_type': self.dic_class} response_dict = self.get_response_dict( relative_url='nlp/v1/keyword', request_body=request_json) self.message = response_dict['message'] self.status = response_dict['status'] self.keyword_result_list = [] for result_dict in response_dict['result']: self.keyword_result_list.append(KeywordResult(result_dict))
def __init__(self, sentence: str, kuzure_flag=False): """ Args: sentence (str): 解析対象文. kuzure_flag (bool, optional): 崩れ文かどうか. Defaults to False. Raises: SentenceTypeError: dic_classにエラーがあります. """ super().__init__() self.sentence = sentence self.sentence_class = get_sentence_class(kuzure_flag) request_json = { 'sentence': self.sentence, 'type': self.sentence_class, } response_dict = self.get_response_dict( relative_url='nlp/v1/sentence_type', request_body=request_json) self.message = response_dict['message'] self.status = response_dict['status'] self.sentence_type_result = SentenceTypeResult(response_dict['result'])