├── README.md
├── src
    ├── __pycache__
    │   └── semantic.cpython-34.pyc
    └── semantic.py
└── test.py


/README.md:
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 1 | 
 2 | ## 语义理解/口语理解
 3 | >>> 采用了深度学习等技术
 4 | 
 5 | 主要功能：
 6 | * 中文分词
 7 | * 词性标注
 8 | * 命名实体识别
 9 | * 领域分类
10 | * 槽填充
11 | * 意图识别
12 | 
13 | 自然语言处理使用的是作者开源的Jiagu项目：https://github.com/ownthink/Jiagu
14 | 
15 | spoken举例：
16 | ```
17 | 上海的天气
18 | 厦门明天会不会下雨
19 | 姚明真正的身高是多少
20 | ```
21 | 
22 | ### 使用方式
23 | ```shell
24 | python3 test.py
25 | ```
26 | 
27 | 解析结果
28 | ```shell
29 | {
30 |     "input": "厦门明天会不会下雨", 
31 |     "semantics": [
32 |         {
33 |             "score": "0.8", 
34 |             "domain": "天气", 
35 |             "intent": "雨", 
36 |             "slot": [
37 |                 [
38 |                     "城市", 
39 |                     "厦门"
40 |                 ], 
41 |                 [
42 |                     "日期", 
43 |                     "明天"
44 |                 ]
45 |             ]
46 |         }
47 |     ], 
48 |     "词法分析": {
49 |         "词性标注": [
50 |             "地名", 
51 |             "时间词", 
52 |             "动词", 
53 |             "动词", 
54 |             "动词"
55 |         ], 
56 |         "实体识别": [
57 |             "B-地名", 
58 |             "O", 
59 |             "O", 
60 |             "O", 
61 |             "O"
62 |         ], 
63 |         "中文分词": [
64 |             "厦门", 
65 |             "明天", 
66 |             "会", 
67 |             "不会", 
68 |             "下雨"
69 |         ]
70 |     }
71 | }
72 | ```
73 | 


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/src/__pycache__/semantic.cpython-34.pyc:
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https://raw.githubusercontent.com/ownthink/Semantic/df9870ad06ef91518654eb117ba7d966f4f76a4f/src/__pycache__/semantic.cpython-34.pyc


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/src/semantic.py:
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 1 | import requests
 2 | 
 3 | class Analysis:
 4 | 	def __init__(self, text):
 5 | 		self.data = None
 6 | 		if text=='' or type(text) != str:
 7 | 			return None
 8 | 		url = 'https://api.ownthink.com/slu?spoken=%s'%text
 9 | 		sess = requests.get(url)
10 | 		text = sess.text
11 | 		slu = eval(text)
12 | 		
13 | 		self.data = slu['data']
14 | 		
15 | 	def analysis(self):
16 | 
17 | 		# 中文分词
18 | 		self.cws = self.data['词法分析']['中文分词']
19 | 		
20 | 		# 词性标注
21 | 		self.pos = self.data['词法分析']['词性标注']
22 | 		
23 | 		# 命名实体识别
24 | 		self.ner = self.data['词法分析']['实体识别']
25 | 		
26 | 		# 领域分类
27 | 		self.domain = self.data['semantics'][0]['domain']
28 | 
29 | 		# 槽填充
30 | 		self.slot = self.data['semantics'][0]['slot']
31 | 
32 | 		# 意图识别
33 | 		self.intent = self.data['semantics'][0]['intent']
34 | 
35 | 		return self.data
36 | 		
37 | 		
38 | 		


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/test.py:
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 1 | from src.semantic import Analysis
 2 | 
 3 | if __name__=='__main__':
 4 | 	
 5 | 	text = '厦门明天会不会下雨'
 6 | 
 7 | 	slu = Analysis(text)
 8 | 	
 9 | 	data = slu.analysis()  #解析
10 | 	print(data) #总的结果
11 | 	
12 | 	print('--------------------------')
13 | 	
14 | 	print(slu.cws) #分词
15 | 	
16 | 	print(slu.pos) #词性标注
17 | 		
18 | 	print(slu.ner) #命名实体识别
19 | 	
20 | 	print(slu.domain) #领域分类
21 | 	
22 | 	print(slu.intent) #意图识别
23 | 	
24 | 	print(slu.slot) #槽填充
25 | 	
26 | 	


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