extractMetric.py 16 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284285286287288289290291292293294295296297298299300301302303304305306307308309310311312313314315316317318319320321322323324325326327328329330331332333334335336337338339340341342343
  1. import psycopg2
  2. from BiddingKG.dl.interface.extract import predict,test
  3. from BiddingKG.dl.common.Utils import getUnifyMoney,timeFormat
  4. import re
  5. import json
  6. class ExtractMetric():
  7. def __init__(self):
  8. self.conn1 = self.getConnection_postgres("iepy")
  9. self.conn2 = self.getConnection_postgres("iepy")
  10. def fitDataByRule(self,data):
  11. symbol_dict = {"(":")",
  12. "(":")",
  13. "[":"]",
  14. "【":"】",
  15. ")":"(",
  16. ")":"(",
  17. "]":"[",
  18. "】":"【"}
  19. leftSymbol_pattern = re.compile("[\((\[【]")
  20. rightSymbol_pattern = re.compile("[\))\]】]")
  21. leftfinds = re.findall(leftSymbol_pattern,data)
  22. rightfinds = re.findall(rightSymbol_pattern,data)
  23. result = data
  24. if len(leftfinds)+len(rightfinds)==0:
  25. return data
  26. elif len(leftfinds)==len(rightfinds):
  27. return data
  28. elif abs(len(leftfinds)-len(rightfinds))==1:
  29. if len(leftfinds)>len(rightfinds):
  30. if symbol_dict.get(data[0]) is not None:
  31. result = data[1:]
  32. else:
  33. #print(symbol_dict.get(leftfinds[0]))
  34. result = data+symbol_dict.get(leftfinds[0])
  35. else:
  36. if symbol_dict.get(data[-1]) is not None:
  37. result = data[:-1]
  38. else:
  39. result = symbol_dict.get(rightfinds[0])+data
  40. return result
  41. def getConnection_postgres(self,db):
  42. conn = psycopg2.connect(dbname=db,user="postgres",password="postgres",host="192.168.2.103")
  43. return conn
  44. def label2interface(self,list_anno,Htext):
  45. dict_result = {}
  46. dict_anno = {}
  47. for _anno in list_anno:
  48. value = _anno["value"]
  49. _split = value.split("\t")
  50. if _split[0][0]=="T":
  51. _type,_begin,_end = _split[1].split(" ")
  52. dict_anno[_split[0]] = {"id":_split[0],"type":_type,"text":_split[2],"begin":int(_begin),"end":int(_end)}
  53. elif _split[0][0]=="R":
  54. _type,arg1,arg2 = _split[1].split(" ")
  55. dict_anno[_split[0]] = {"id":_split[0],"type":_type,"arg1":arg1.split(":")[1],"arg2":arg2.split(":")[1]}
  56. dict_role = {}
  57. dict_money = {}
  58. dict_person2role = {}
  59. dict_name_freq_score = {}
  60. pattern_score = re.compile("工程|服务|采购|施工|项目|系统|招标|中标|公告|学校|[大中小]学校?|医院|公司|分公司|研究院|政府采购中心|学院|中心校?|办公室|政府|财[政务]局|办事处|委员会|[部总支]队|警卫局|幼儿园|党委|党校|银行|分行|解放军|发电厂|供电局|管理所|供电公司|卷烟厂|机务段|研究[院所]|油厂|调查局|调查中心|出版社|电视台|监狱|水厂|服务站|信用合作联社|信用社|交易所|交易中心|交易中心党校|科学院|测绘所|运输厅|管理处|局|中心|机关|部门?|处|科|厂|集团|图书馆|馆|所|厅|楼|区|酒店|场|基地|矿|餐厅|酒店")
  61. for k,v in dict_anno.items():
  62. if v.get("type") in ["code","product","person_review"]:
  63. if v.get("type") not in dict_result:
  64. dict_result[v.get("type")] = []
  65. dict_result[v.get("type")].append(v.get("text"))
  66. dict_result[v.get("type")] = list(set(dict_result[v.get("type")]))
  67. if v.get("type") in ["name","bidway","moneysource","serviceTime","time_release","time_bidopen","time_bidclose"]:
  68. if v.get("type")=="name":
  69. _name = self.fitDataByRule(v.get("text"))
  70. w = 1 if re.search('(项目|工程|招标|合同|标项|标的|计划|询价|询价单|询价通知书|申购)(名称|标题|主题)[::\s]', _name)!=None else 0.5
  71. if _name not in dict_name_freq_score:
  72. # dict_name_freq_score[_name] = [1,len(re.findall(pattern_score,_name))+len(_name)*0.1]
  73. dict_name_freq_score[_name] = [1, (len(re.findall(pattern_score, _name)) + len(_name) * 0.05)*w]
  74. else:
  75. dict_name_freq_score[_name][0] += 1
  76. max_score = 0
  77. for _k1,_v1 in dict_name_freq_score.items():
  78. if _v1[0]*_v1[1]>max_score:
  79. max_score = _v1[0]*_v1[1]
  80. dict_result[v.get("type")] = _k1
  81. if v.get("type") not in dict_result:
  82. if v.get("type") in ["time_release","time_bidopen","time_bidclose"]:
  83. _t = timeFormat(v.get("text"))
  84. else:
  85. _t = v.get("text")
  86. dict_result[v.get("type")] = _t
  87. _split = v.get("type").split("_")
  88. if len(_split)>1:
  89. if _split[1]=="tenderee":
  90. dict_role["tenderee"] = {"subject":v.get("text")}
  91. if _split[1]=="agency":
  92. dict_role["agency"] = {"subject":v.get("text")}
  93. if _split[1]=="tenderer":
  94. dict_role["tenderer"] = {"subject":v.get("text")}
  95. if _split[1]=="secondTenderer":
  96. dict_role["secondTenderer"] = {"subject":v.get("text")}
  97. if _split[1]=="thirdTenderer":
  98. dict_role["thirdTenderer"] = {"subject":v.get("text")}
  99. tendereeMoney = 0
  100. for k,v in dict_anno.items():
  101. _split = v.get("type").split("_")
  102. if v.get("type") in ["money_tendereeMoney"]:
  103. _before_text = Htext[max(v["begin"]-10,0):v["begin"]]
  104. if re.search("万",_before_text) is not None and re.search("整",_before_text) is None:
  105. _unit = 10000
  106. else:
  107. _unit = 1
  108. tendereeMoney = float(getUnifyMoney(v["text"])*_unit)
  109. if v.get("type") in ["rel_tendereeMoney","rel_tendererMoney"]:
  110. arg1 = v.get("arg1")
  111. arg2 = v.get("arg2")
  112. for _k,_v in dict_role.items():
  113. if _v["subject"]==dict_anno[arg1]["text"]:
  114. _before_text = Htext[max(dict_anno[arg2]["begin"]-10,0):dict_anno[arg2]["begin"]]
  115. if re.search("万",_before_text) is not None and re.search("整",_before_text) is None:
  116. _unit = 10000
  117. else:
  118. _unit = 1
  119. _v["money"] = float(getUnifyMoney(dict_anno[arg2]["text"])*_unit)
  120. if v.get("type")=="person_tendereePerson":
  121. if "tenderee" in dict_role:
  122. if "person" not in dict_role["tenderee"]:
  123. dict_role["tenderee"]["person"] = []
  124. dict_role["tenderee"]["person"].append({"person":v["text"]})
  125. if v.get("type")=="person_agencyPerson":
  126. if "agency" in dict_role:
  127. if "person" not in dict_role["agency"]:
  128. dict_role["agency"]["person"] = []
  129. dict_role["agency"]["person"].append({"person":v["text"]})
  130. if v.get("type")=="rel_person":
  131. arg1 = v.get("arg1")
  132. arg2 = v.get("arg2")
  133. for _k,_v in dict_role.items():
  134. if _v["subject"]==dict_anno[arg1]["text"]:
  135. if "person" not in dict_role[_k]:
  136. dict_role[_k]["person"] = []
  137. dict_role[_k]["person"].append({"person":dict_anno[arg2]["text"]})
  138. dict_person2role[dict_anno[arg2]["text"]] = _k
  139. for k,v in dict_anno.items():
  140. if v.get("type")=="rel_phone":
  141. arg1 = v.get("arg1")
  142. arg2 = v.get("arg2")
  143. _person = dict_anno[arg1]["text"]
  144. if _person in dict_person2role:
  145. for item in dict_role[dict_person2role[_person]]["person"]:
  146. if item["person"]==_person:
  147. item["phone"] = dict_anno[arg2]["text"]
  148. roleList = []
  149. for k,v in dict_role.items():
  150. if k=="tenderee":
  151. _role = "tenderee"
  152. if k=="agency":
  153. _role = "agency"
  154. if k=="tenderer":
  155. _role = "win_tenderer"
  156. if k=="secondTenderer":
  157. _role = "second_tenderer"
  158. if k=="thirdTenderer":
  159. _role = "third_tenderer"
  160. list_person = []
  161. set_person = set()
  162. for item in v.get("person",[]):
  163. if item["person"] not in set_person:
  164. list_person.append([item["person"],item.get("phone","")])
  165. set_person.add(item["person"])
  166. roleList.append([_role,v.get("subject","").replace("(","(").replace(")",")"),v.get("money",0),list_person,""])
  167. dict_result["prem"] = {"Project":{"roleList":roleList,"tendereeMoney":tendereeMoney}}
  168. return dict_result
  169. def culExtractMetrics(self):
  170. conn = self.conn1
  171. cursor = conn.cursor()
  172. sql = ' select begin_time,end_time,"user",doc_count from corpus_payroll where end_time<=\'2021-07-25\' order by end_time desc limit 20'
  173. cursor.execute(sql)
  174. list_diff = []
  175. rows_payroll = cursor.fetchall()
  176. for _payroll in rows_payroll:
  177. _begin_time = _payroll[0]
  178. _end_time = _payroll[1]
  179. _user = _payroll[2]
  180. doc_count = _payroll[3]
  181. print(_user,_begin_time,_end_time,doc_count)
  182. _sql = "select document_id,value from brat_bratannotation where document_id in (select human_identifier from corpus_iedocument where edituser='%s' and to_char(edittime,'yyyy-mm-dd')>='%s' and to_char(edittime,'yyyy-mm-dd')<='%s' limit 100) order by document_id"%(_user,_begin_time,_end_time)
  183. cursor.execute(_sql)
  184. rows = cursor.fetchall()
  185. if len(rows)>0:
  186. current_docid = rows[0][0]
  187. _index = -1
  188. list_values = []
  189. while _index<len(rows)-1:
  190. _index += 1
  191. row = rows[_index]
  192. document_id = row[0]
  193. value = row[1]
  194. if document_id!=current_docid:
  195. print(current_docid)
  196. sql = "select text from corpus_iedocument where human_identifier='%s'"%(str(current_docid))
  197. cursor.execute(sql)
  198. content = cursor.fetchall()[0][0]
  199. _inter = self.label2interface(list_values,content)
  200. _inter2 = self.extractFromInterface(content)
  201. if not len(_inter2.get("prem").keys())>1:
  202. _diff = self.getDiff(_inter,_inter2)
  203. list_diff.append(_diff)
  204. _index -= 1
  205. current_docid = document_id
  206. list_values = []
  207. else:
  208. list_values.append({"document_id":document_id,"value":value})
  209. metrics = self.getMetrics(list_diff)
  210. print(metrics)
  211. def extractFromInterface(self,content):
  212. return json.loads(test("",content))
  213. def getDiff(self,_inter,_inter2):
  214. _dict = {}
  215. for k in ["code","product","person_review"]:
  216. set_k1 = _inter.get(k,set())
  217. set_k2 = _inter2.get(k,set())
  218. _dict["%s_inter"%k] = len(set_k1)
  219. _dict["%s_inter2"%k] = len(set_k2)
  220. _dict["%s_union"%k] = len(set(set_k1)&set(set_k2))
  221. for k in ["name","bidway","moneysource","serviceTime","time_release","time_bidopen","time_bidclose"]:
  222. _k1 = _inter.get(k,"")
  223. _k2 = _inter2.get(k,"")
  224. len_k1 = 0 if _k1=="" else 1
  225. len_k2 = 0 if _k2=="" else 1
  226. len_union = 1 if _k1==_k2 and len_k1==1 else 0
  227. _dict["%s_inter"%k] = len_k1
  228. _dict["%s_inter2"%k] = len_k2
  229. _dict["%s_union"%k] = len_union
  230. dict_project = {}
  231. for k,v in _inter.get("prem",{}).items():
  232. if float(v.get("tendereeMoney",0))>0:
  233. dict_project["%s_inter"%("tendereeMoney")] = [float(v.get("tendereeMoney"))]
  234. for _role in v.get("roleList",[]):
  235. dict_project["%s_inter"%_role[0]] = [_role[1]]
  236. if _role[0] in ["win_tenderer","second_tenderer","third_tenderer"]:
  237. if float(_role[2])>0:
  238. dict_project["%s_money_inter"%_role[0]] = [float(_role[2])]
  239. for item in _role[3]:
  240. _person = item[0]
  241. _phone = item[1]
  242. if _person=="" or _phone=="":
  243. continue
  244. if "%s_person_inter"%_role[0] not in dict_project:
  245. dict_project["%s_person_inter"%_role[0]] = []
  246. dict_project["%s_person_inter"%_role[0]].append("%s-%s"%(_role[1],_person))
  247. if "person_phone_inter" not in dict_project:
  248. dict_project["person_phone_inter"] = []
  249. dict_project["person_phone_inter"].append("%s-%s"%(_person,_phone))
  250. for k,v in _inter2.get("prem",{}).items():
  251. if float(v.get("tendereeMoney",0))>0:
  252. dict_project["%s_inter2"%("tendereeMoney")] = [float(v.get("tendereeMoney"))]
  253. for _role in v.get("roleList",[]):
  254. dict_project["%s_inter2"%_role[0]] = [_role[1]]
  255. if _role[0] in ["win_tenderer","second_tenderer","third_tenderer"]:
  256. if float(_role[2])>0:
  257. dict_project["%s_money_inter2"%_role[0]] = [float(_role[2])]
  258. for item in _role[3]:
  259. _person = item[0]
  260. _phone = item[1]
  261. if _person=="" or _phone=="":
  262. continue
  263. if "%s_person_inter2"%_role[0] not in dict_project:
  264. dict_project["%s_person_inter2"%_role[0]] = []
  265. dict_project["%s_person_inter2"%_role[0]].append("%s-%s"%(_role[1],_person))
  266. if "person_phone_inter2" not in dict_project:
  267. dict_project["person_phone_inter2"] = []
  268. dict_project["person_phone_inter2"].append("%s-%s"%(_person,_phone))
  269. set_k = set()
  270. for k,v in dict_project.items():
  271. k_split = k.split("_")
  272. base_key = "_".join(k_split[:-1])
  273. if k_split[-1]=="inter":
  274. k2 = "inter2"
  275. else:
  276. k2 = "inter"
  277. if base_key in set_k:
  278. continue
  279. k_other = "%s_%s"%(base_key,k2)
  280. _dict[k] = len(v)
  281. _dict[k_other] = len(dict_project.get(k_other,[]))
  282. _dict["%s_union"%base_key] = len(set(v)&set(dict_project.get(k_other,[])))
  283. set_k.add(base_key)
  284. print("=========================")
  285. print(_inter)
  286. print("-----")
  287. print(_inter2)
  288. print("|||||")
  289. print(_dict)
  290. return _dict
  291. def getMetrics(self,list_diff):
  292. dict_key_count = {}
  293. print("all_count:",list_diff)
  294. for _diff in list_diff:
  295. for k,v in _diff.items():
  296. if k not in dict_key_count:
  297. dict_key_count[k] = 0
  298. dict_key_count[k] += v
  299. set_k = set()
  300. for k,v in dict_key_count.items():
  301. k_split = k.split("_")
  302. base_k = "_".join(k_split[:-1])
  303. if base_k in set_k:
  304. continue
  305. set_k.add(base_k)
  306. _count_inter = max(dict_key_count.get("%s_inter"%base_k,-1),1)
  307. _count_inter2 = max(dict_key_count.get("%s_inter2"%base_k,-1),1)
  308. _count_union = dict_key_count.get("%s_union"%base_k,0)
  309. _precision = _count_union/_count_inter2
  310. _recall = _count_union/_count_inter
  311. _f1 = 2*(_precision*_recall)/(_precision+_recall)
  312. print("%s: recall:%.3f,precision:%.3f,f1_score:%.3f"%(base_k,_recall,_precision,_f1))
  313. print(base_k)
  314. print("%.3f"%_f1)
  315. print("%.3f"%_precision)
  316. print("%.3f"%_recall)
  317. if __name__=="__main__":
  318. em = ExtractMetric()
  319. em.culExtractMetrics()