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'])