def run_main(self):
# TODO 连接Fuseki服务器。
fuseki = jena_sparql_endpoint.JenaFuseki()
# TODO 初始化自然语言到SPARQL查询的模块，参数是外部词典列表。
q2s = question2sparql.Question2Sparql(['./util/shop_title.txt'])
my_query = q2s.get_sparql(self.question)
if my_query is not None:
result = fuseki.get_sparql_result(my_query)
value = fuseki.get_sparql_result_value(result)
# TODO 判断结果是否是布尔值，是布尔值则提问类型是"ASK"，回答“是”或者“不知道”。
if isinstance(value, bool):
if value is True:
return 'Yes'
else:
return 'I don\'t know. :('
else:
# TODO 查询结果为空，根据OWA，回答“不知道”
if len(value) == 0:
return 'I don\'t know. :('
elif len(value) == 1:
return value[0]
else:
output = ''
for v in value:
output += v + u'、'
return output[0:-1]
else:
# TODO 自然语言问题无法匹配到已有的正则模板上，回答“无法理解”
return 'I can\'t understand. :('
def __init__(self, dict_path):
self.q2s = question2sparql.Question2Sparql(dict_path)
self.fuseki = jena_sparql_endpoint.JenaFuseki()
self.unknown_responses = [
'我现在还不知道，等我多学一点再告诉你。 ;-)', '渊博如我竟也不知道，你该不是刁难我吧。。。'
]
self.cant_understand_responses = [
'不是我不知道，只是我现在还没办法理解你的意思。:-(', '不好意思，我还没办法理解你的问题。:-('
]
print('Sparql endpoint starts successfully!')
def query():
#连接Fuseki服务器。
fuseki = jena_sparql_endpoint.JenaFuseki()
#初始化自然语言到SPARQL查询的模块，参数是外部词典列表。
q2s = question2sparql.Question2Sparql([
'./external_dict/company.txt', './external_dict/servicetype.txt',
'./external_dict/service.txt'
])
question = request.args.get('q')
my_query = q2s.get_sparql(question)
print('查询语句:', my_query, '\n')
qtype = 1
if my_query is not None:
result = fuseki.get_sparql_result(my_query)
# value = fuseki.get_sparql_result_value(result)
#query_result为列表 元素是字典
query_head, query_result = fuseki.parse_result(result)
print('结果', query_head, query_result)
if query_head is None:
#ASK类型问题
if query_result is True:
answer = 'Yes'
else:
answer = 'I don\'t know. :('
else:
if query_result == []:
answer = 'I don\'t know. :('
#查询单个属性 单个值
else:
if len(query_head) == 1 and len(query_result) == 1:
head = query_head[0]
answer = query_result[0][head]
#查询多个属性
else:
temp = list()
qtype = 2
for qr in query_result:
temp.append(json.dumps(qr))
return json.dumps({
'type': qtype,
'head': query_head,
'answer': temp
})
else:
# TODO 自然语言问题无法匹配到已有的正则模板上，回答“无法理解”
qtype = 0
answer = 'I don\'t understand. :('
return json.dumps({'type': qtype, 'answer': answer})
def searchMain(question):
# 连接Fuseki服务器。
fuseki = jena_sparql_endpoint.JenaFuseki()
# 初始化自然语言到SPARQL查询的模块，参数是外部词典列表。
q2s = question2sparql.Question2Sparql([
'./cmdb/query/external_dict/drug_name.txt',
'./cmdb/query/external_dict/person_name.txt',
'./cmdb/query/external_dict/case_name.txt',
'./cmdb/query/external_dict/drug_to_person.txt'
])
my_query = q2s.get_sparql(question.decode('utf-8')) #sparql查询语句
# print my_query
if my_query is not None:
result = fuseki.get_sparql_result(my_query)
value = fuseki.get_sparql_result_value(result)
# print value
# 判断结果是否是布尔值，是布尔值则提问类型是"ASK"，回答“是”或者“不知道”。
if isinstance(value, bool):
if value is True:
# print 'Yes'
re = 'Yes:)'
else:
# print 'I don\'t know. :('
re = 'I don\'t know. :('
else:
# 查询结果为空，根据OWA，回答“不知道”
if len(value) == 0:
# print 'I don\'t know. :('
re = 'I don\'t know. :('
elif len(value) == 1:
# print value[0]
re = value[0]
else:
output = ''
for v in value:
output += v + u'、'
# print output[0:-1]
re = output[0:-1]
else:
# 自然语言问题无法匹配到已有的正则模板上，回答“无法理解”
# print 'I can\'t understand. :('
re = 'I can\'t understand. :('
return re
# encoding=utf-8
"""
输入一个问题， 通过RDF模型，查询答案
"""
import jena_sparql_endpoint
import question2sparql
import datetime
if __name__ == '__main__':
# TODO 连接Fuseki服务器。
fuseki = jena_sparql_endpoint.JenaFuseki()
# TODO 初始化自然语言到SPARQL查询的模块，参数是外部词典列表。
q2s = question2sparql.Question2Sparql(
['./external_dict/movie_title.txt', './external_dict/person_name.txt'])
while True:
question = input() # 输入问题
my_query = q2s.get_sparql(question)
if my_query is not None:
result = fuseki.get_sparql_result(my_query[0])
value = fuseki.get_sparql_result_value(result)
# TODO 判断结果是否是布尔值，是布尔值则提问类型是"ASK"，回答“是”或者“不知道”。
if isinstance(value, bool):
if value is True:
print('Yes')
else:
print('I don\'t know. :(')