def floor_dict_match(cls, question_str, var_list, graph):
dict_list = rdfPrepare.rdf_query_varientnames('floor', graph)
entities = DictMatch2.floor_dict_match(question_str, var_list, graph)
for i in range(len(entities)):
for entity in entities[i]:
dict_list[entity].sort(key=lambda s: len(s), reverse=True)
for varname in dict_list[entity]:
question_str = question_str.replace(
varname, replace_entity_mark['floor'])
return question_str, entities
def room_dict_match(cls, question_str, var_list, graph):
dict_list = rdfPrepare.rdf_query_varientnames('room', graph)
#print("dict_list",dict_list)
entities = DictMatch2.room_dict_match(question_str, var_list, graph)
for i in range(len(entities)):
for entity in entities[i]:
#print("dict_list[entity]",type(dict_list[entity]))
dict_list[entity].sort(key=lambda s: len(s), reverse=True)
for varname in dict_list[entity]:
question_str = question_str.replace(
varname, replace_entity_mark['room'])
return question_str, entities
def match_and_replace_all(cls, question_str, graph):
"""
对问句进行所有类型实体匹配与替换
:param question_str:
:return:
"""
entity_dict = {} #分类存放匹配到的各类实体
var_list = DictMatch2.var_dict_list(graph)
question_str, entity_list = cls.room_dict_match(
question_str, var_list, graph)
entity_dict['room'] = entity_list
question_str, entity_list = cls.resource_dict_match(
question_str, var_list, graph)
entity_dict['res'] = entity_list
question_str, entity_list = cls.floor_dict_match(
question_str, var_list, graph)
entity_dict['floor'] = entity_list
return question_str, entity_dict