BIDI_ML_INFO_EXTRACTION/BiddingKG/dl/interface/getAttributes.py

from BiddingKG.dl.common.Utils import findAllIndex,debug,timeFormat,getCurrent_date
from BiddingKG.dl.interface.Entitys import PREM,Role,Entity
from decimal import Decimal
import re
import copy
import math
import pandas as pd
import os
from scipy.optimize import linear_sum_assignment
from BiddingKG.dl.interface.Entitys import Match
import numpy as np

def getTheRole(entity,role_list):
    '''
    @summary:根据实体名称拿到index
    @param:
        entity:实体名称
        role_list:角色list
    @return:该实体所在下标
    '''
    for role_index in range(len(role_list)):
        if entity in role_list[role_index]:
            return role_index
    return None

dict_role_id = {"0":"tenderee",
                "1":"agency",
                "2":"win_tenderer",
                "3":"second_tenderer",
                "4":"third_tenderer"}

def getPackage(packageList,sentence_index,begin_index,roleid,MAX_DIS=None,DIRECT=None):
    '''
    @param:
        packageList:文章的包的信息,包号-sent_index-词偏移-字偏移-[[前作用域句子,句内偏移],[后作用域句子,句内偏移]]-匹配集合
        sentence_index:实体所在的句子
        begin_index:实体所在句子的起始位置
    @return:公司实体所属的包
    @summary: 优化多标段，确定标段作用域之后，寻找作用域包含该实体的所有包，从前往后找到一个还没有该roleid的包返回，若找到的包都有roleid,则返回第一个，若没有找到包，返回None
    '''
    
    '''
    if len(packageList)==0:
        return None
    before_index = None
    after_index = None
    equal_index = None
    equal_count = 0
    
    
    for pack_index in range(len(packageList)):
        if packageList[pack_index][1]>sentence_index and after_index is None:
            after_index = pack_index
        if packageList[pack_index][1]<sentence_index:
            before_index = pack_index
        if packageList[pack_index][1]==sentence_index and equal_index is None:
            equal_index = pack_index
    #当前句子和之前句子未找到包
    if before_index is None and equal_index is None:
        return None
    else:
        if after_index is None:
            end_index = len(packageList)
        else:
            end_index = after_index
        #只在当前句子找到一个包号
        if end_index-max((before_index if before_index is not None else -1,equal_index if equal_index is not None else -1))==1:
            return packageList[end_index-1][0]
        else:
            for i in range(max((before_index if before_index is not None else -1,equal_index if equal_index is not None else -1)),end_index):
                if packageList[i][2]>int(begin_index):
                    if packageList[i-1][4]:
                        return packageList[i-1][0]
                    else:
                        if packageList[i][4]:
                            return packageList[i-1][0]
                        else:
                            return packageList[i][0]
            return packageList[end_index-1][0]
    '''
    if len(packageList)==0:
        return None,False
    list_legalPack = []
    for pack_index in range(len(packageList)):
        if DIRECT=="L" and (packageList[pack_index]["sentence_index"]>sentence_index or (packageList[pack_index]["sentence_index"]==sentence_index and packageList[pack_index]["offsetWords_begin"]>begin_index)):
            continue
        if DIRECT=="R" and (packageList[pack_index]["sentence_index"]<sentence_index or (packageList[pack_index]["sentence_index"]==sentence_index and packageList[pack_index]["offsetwords_begin"]<begin_index)):
            continue
        if (packageList[pack_index]["scope"][0][0]<sentence_index or (packageList[pack_index]["scope"][0][0]==sentence_index and packageList[pack_index]["scope"][0][1]<=begin_index))  and (packageList[pack_index]["scope"][1][0]>sentence_index or (packageList[pack_index]["scope"][1][0]==sentence_index and packageList[pack_index]["scope"][1][1]>=begin_index)):
            if MAX_DIS is not None:
                if abs(sentence_index-packageList[pack_index]["sentence_index"])<=MAX_DIS:
                    list_legalPack.append(pack_index)
            else:
                list_legalPack.append(pack_index)
    # if (packageList[pack_index]["scope"][0][0] < sentence_index
    #         or (packageList[pack_index]["scope"][0][0] == sentence_index
    #      and packageList[pack_index]["scope"][0][1] <= begin_index))
    #         and (packageList[pack_index]["scope"][1][0] > sentence_index
    #      or (packageList[pack_index]["scope"][1][0] == sentence_index
    #         and packageList[pack_index]["scope"][1][1] >= begin_index)):
    #     pass
    _flag = True
    for _index in list_legalPack:
        if roleid in packageList[_index]["hit"]:
            continue
        else:
            _flag = False
            packageList[_index]["hit"].add(roleid)
            return packageList[_index]["pointer"],_flag
    if len(list_legalPack)>0:
        return packageList[0]["pointer"],_flag
    return None,False

#生成合法的组合
def get_legal_comba(list_entity,dict_role_combination):
    
    #拿到一个包中所有合法的组合
    def circle_package(_dict_legal_combination):
        list_dict_role_first = []
        for _role in _dict_legal_combination:
            if len(list_dict_role_first)==0:
                for _entity in _dict_legal_combination[_role]:
                    if _entity !="":
                        list_dict_role_first.append({_role:_entity})
            else:
                list_dict_role_after = []
                _find_count = 0
                for _entity in _dict_legal_combination[_role]:
                    if _entity !="":
                        for _dict in list_dict_role_first:
                            _flag = True
                            for _key1 in _dict:
                                if _entity==_dict[_key1]:
                                    #修改为招标人和代理人可以为同一个
                                    if str(_key1) in ["0","1"] and str(_role) in ["0","1"]:
                                        _flag = True
                                    else:
                                        _flag = False
                            if _flag:
                                _find_count += 1
                                _new_dict = copy.copy(_dict)
                                _new_dict[_role] = _entity
                                if len(list_dict_role_after)>100000:
                                    break
                                list_dict_role_after.append(_new_dict)
                            else:
                                # 2021/5/25 update,同一实体（entity_text）不同角色
                                if len(list_dict_role_after) > 100000:
                                    break
                                for _dict in list_dict_role_first:
                                    for _key1 in _dict:
                                        if _entity == _dict[_key1]:
                                            _new_dict = copy.copy(_dict)
                                            _new_dict.pop(_key1)
                                            _new_dict[_role] = _entity
                                            list_dict_role_after.append({_role:_entity})
                if len(list_dict_role_after)==0:
                    pass
                else:
                    list_dict_role_first.extend(list_dict_role_after)

        return list_dict_role_first



    def recursive_package(_dict_legal_combination,set_legal_entity,dict_one_selution,list_all_selution):
        last_layer = False
        #若是空组合则放回空
        if len(_dict_legal_combination.keys())==0:
            return []
        #递归到最后一层则修改状态
        if len(_dict_legal_combination.keys())==1:
            last_layer = True
        #取一个角色开始进行遍历
        _key_role = list(_dict_legal_combination.keys())[0]
        for item in _dict_legal_combination[_key_role]:
            copy_dict_one_selution = copy.copy(dict_one_selution)
            copy_dict_legal_combination = {}
            copy_set_legal_entity = copy.copy(set_legal_entity)
            
            #复制余下的所有角色，进行下一轮递归
            for _key in _dict_legal_combination.keys():
                if _key!=_key_role:
                    copy_dict_legal_combination[_key] = _dict_legal_combination[_key]

            #修改为招标人和代理人可以为同一个
            if item !="":
                _flag = True
                if str(_key_role) in ["0","1"]:
                    for _key_flag in copy_dict_one_selution:
                        if _key_flag not in ["0","1"] and copy_dict_one_selution[_key_flag]==item:
                            _flag = False
                else:
                    for _key_flag in copy_dict_one_selution:
                        if copy_dict_one_selution[_key_flag]==item:
                            _flag = False
                if _flag:
                    copy_dict_one_selution[_key_role] = item
                    
            '''
            if item not in copy_set_legal_entity:
                if item !="":
                    copy_dict_one_selution[_key_role] = item
            '''
            copy_set_legal_entity.add(item)
            if last_layer:
                list_all_selution.append(copy_dict_one_selution)
            else:
                recursive_package(copy_dict_legal_combination,copy_set_legal_entity,copy_dict_one_selution,list_all_selution)
    

    #递归匹配各个包的结果        
    def recursive_packages(_dict_legal_combination,dict_one_selution,list_all_selution):
        last_layer = False
        if len(_dict_legal_combination.keys())==0:
            return []
        if len(_dict_legal_combination.keys())==1:
            last_layer = True
        _key_pack = list(_dict_legal_combination.keys())[0]
        for item in _dict_legal_combination[_key_pack]:
            copy_dict_one_selution = copy.copy(dict_one_selution)
            copy_dict_legal_combination = {}
            for _key in _dict_legal_combination.keys():
                if _key!=_key_pack:
                    copy_dict_legal_combination[_key] = _dict_legal_combination[_key]
            for _key_role in item.keys():
                copy_dict_one_selution[_key_pack+"$$"+_key_role] = item[_key_role]
            if last_layer:
                list_all_selution.append(copy_dict_one_selution)
            else:
                recursive_packages(copy_dict_legal_combination,copy_dict_one_selution,list_all_selution)
        return list_all_selution
    
    #循环获取所有包组合
    def circle_pageages(_dict_legal_combination):
        list_all_selution = []
        for _key_pack in _dict_legal_combination.keys():
            list_key_selution = []
            for item in _dict_legal_combination[_key_pack]:
                _dict = dict()
                for _key_role in item.keys():
                    _dict[_key_pack+"$$"+_key_role] = item[_key_role]
                list_key_selution.append(_dict)
            if len(list_all_selution)==0:
                list_all_selution = list_key_selution
            else:
                _list_all_selution = []
                for item_1 in list_all_selution:
                    for item_2 in list_key_selution:
                        _list_all_selution.append(dict(item_1,**item_2))
                list_all_selution = _list_all_selution
        return list_all_selution
                      
    #拿到各个包解析之后的结果
    _dict_legal_combination = {}
    for packageName in dict_role_combination.keys():
        _list_all_selution = []

        # recursive_package(dict_role_combination[packageName], set(), {}, _list_all_selution)
        _list_all_selution = circle_package(dict_role_combination[packageName])
        '''
        # print("===1")
        # print(packageName)
        for item in _list_all_selution:
            # print(item)
        # print("===2")
        '''
        #去除包含子集
        list_all_selution_simple = []
        _list_set_all_selution = []
        for item_selution in _list_all_selution:
            item_set_selution = set()
            for _key in item_selution.keys():
                item_set_selution.add((_key,item_selution[_key]))
            _list_set_all_selution.append(item_set_selution)
        if len(_list_set_all_selution)>1000:
            _dict_legal_combination[packageName] = _list_all_selution
            continue
        for i in range(len(_list_set_all_selution)):
            
            be_included = False
            for j in range(len(_list_set_all_selution)):
                if i!=j:
                    if len(set(_list_set_all_selution[i])&set(_list_set_all_selution[j]))==len(_list_set_all_selution[i]) and len(_list_set_all_selution[i])!=len(_list_set_all_selution[j]):
                        be_included = True
            if not be_included:
                list_all_selution_simple.append(_list_all_selution[i])
        _dict_legal_combination[packageName] = list_all_selution_simple
    _list_final_comba = []
    #对各个包的结果进行排列组合
    _comba_count = 1
    for _key in _dict_legal_combination.keys():
        _comba_count *= len(_dict_legal_combination[_key])
    #如果过大，则每个包只取概率最大的那个
    dict_pack_entity_prob = get_dict_entity_prob(list_entity)
    if _comba_count>250:
        new_dict_legal_combination = dict()
        for _key_pack in _dict_legal_combination.keys():
            MAX_PROB = -1000
            _MAX_PROB_COMBA = None
            for item in _dict_legal_combination[_key_pack]:
                # print(_key_pack,item)
                _dict = dict()
                for _key in item.keys():
                    _dict[str(_key_pack)+"$$"+str(_key)] = item[_key]
                _prob = getSumExpectation(dict_pack_entity_prob, _dict)
                if _prob>MAX_PROB:
                    MAX_PROB = _prob
                    _MAX_PROB_COMBA = [item]
            if _MAX_PROB_COMBA is not None:
                new_dict_legal_combination[_key_pack] = _MAX_PROB_COMBA
        _dict_legal_combination = new_dict_legal_combination
    #recursive_packages(_dict_legal_combination, {}, _list_final_comba)
    _list_final_comba = circle_pageages(_dict_legal_combination)
    #除了Project包(招标人和代理人)，其他包是不会有冲突的
    #查看是否有一个实体出现在了Project包和其他包中，如有，要进行裁剪
    _list_real_comba = []
    for dict_item in _list_final_comba:
        set_project = set()
        set_other = set()
        for _key in list(dict_item.keys()):
            if _key.split("$$")[0]=="Project":
                set_project.add(dict_item[_key])
            else:
                set_other.add(dict_item[_key])
        set_common = set_project&set_other
        if len(set_common)>0:
            dict_project = {}
            dict_not_project = {}
            for _key in list(dict_item.keys()):
                if dict_item[_key] in set_common:
                    if str(_key.split("$$")[0])=="Project":
                        dict_project[_key] = dict_item[_key]
                    else:
                        dict_not_project[_key] = dict_item[_key]
                else:
                    dict_project[_key] = dict_item[_key]
                    dict_not_project[_key] = dict_item[_key]
            
            _list_real_comba.append(dict_project)
            _list_real_comba.append(dict_not_project)
        else:
            _list_real_comba.append(dict_item)

    return _list_real_comba

def get_dict_entity_prob(list_entity,on_value=0.5):
    dict_pack_entity_prob = {}
    for entity in list_entity:
        if entity.entity_type in ['org','company']:
            values = entity.values
            role_prob = float(values[int(entity.label)])
            _key = entity.packageName+"$$"+str(entity.label)
            if role_prob>=on_value and str(entity.label)!="5":
                _key_prob = _key+"$text$"+entity.entity_text
                if _key_prob in dict_pack_entity_prob:
                    if role_prob>dict_pack_entity_prob[_key_prob][1]:
                        dict_pack_entity_prob[_key_prob] = [entity.entity_text,role_prob]
                else:
                    dict_pack_entity_prob[_key_prob] = [entity.entity_text,role_prob]
    return dict_pack_entity_prob


#计算合计期望            
def getSumExpectation(dict_pack_entity_prob,combination,on_value=0.5):
    '''
    expect = 0
    for entity in list_entity:
        if entity.entity_type in ['org','company']:
            values = entity.values
            role_prob = float(values[int(entity.label)])
            _key = entity.packageName+"$$"+str(entity.label)
            if role_prob>on_value and str(entity.label)!="5":
                if _key in combination.keys() and combination[_key]==entity.entity_text:
                    expect += math.pow(role_prob,4)
                else:
                    expect -= math.pow(role_prob,4)
    '''
    #修改为同一个实体只取对应包-角色的最大的概率值
    expect = 0
    dict_entity_prob = {}
    for _key_pack_entity in dict_pack_entity_prob:
        _key_pack = _key_pack_entity.split("$text$")[0]
        role_prob = dict_pack_entity_prob[_key_pack_entity][1]
        if _key_pack in combination.keys() and combination[_key_pack]==dict_pack_entity_prob[_key_pack_entity][0]:
            if _key_pack_entity in dict_entity_prob.keys():
                if dict_entity_prob[_key_pack_entity]<role_prob:
                    dict_entity_prob[_key_pack_entity] = role_prob
            else:
                dict_entity_prob[_key_pack_entity] = role_prob
        else:
            if _key_pack_entity in dict_entity_prob.keys():
                if dict_entity_prob[_key_pack_entity]>-role_prob:
                    dict_entity_prob[_key_pack_entity] = -role_prob
            else:
                dict_entity_prob[_key_pack_entity] = -role_prob
    # for entity in list_entity:
    #     if entity.entity_type in ['org','company']:
    #         values = entity.values
    #         role_prob = float(values[int(entity.label)])
    #         _key = entity.packageName+"$$"+str(entity.label)
    #         if role_prob>=on_value and str(entity.label)!="5":
    #             if _key in combination.keys() and combination[_key]==entity.entity_text:
    #                 _key_prob = _key+entity.entity_text
    #                 if _key_prob in dict_entity_prob.keys():
    #                     if dict_entity_prob[_key_prob]<role_prob:
    #                         dict_entity_prob[_key_prob] = role_prob
    #                 else:
    #                     dict_entity_prob[_key_prob] = role_prob
    #             else:
    #                 _key_prob = _key+entity.entity_text
    #                 if _key_prob in dict_entity_prob.keys():
    #                     if dict_entity_prob[_key_prob]>-role_prob:
    #                         dict_entity_prob[_key_prob] = -role_prob
    #                 else:
    #                     dict_entity_prob[_key_prob] = -role_prob
    for _key in dict_entity_prob.keys():
        symbol = 1 if dict_entity_prob[_key]>0 else -1 
        expect += symbol*math.pow(dict_entity_prob[_key],2)
    return expect


def getRoleList(list_sentence,list_entity,on_value = 0.5):
    '''
    @summary: 搜索树，得到所有不矛盾的角色组合，取合计期望值最大的作为结果返回
    @param:
        list_sentence:文章所有的sentence
        list_entity:文章所有的实体
        on_value:概率阈值
    @return:文章的角色list
    '''

    pack = getPackagesFromArticle(list_sentence,list_entity)
    if pack is None:
        return None
    PackageList,PackageSet,dict_PackageCode = pack

    #拿到所有可能的情况
    dict_role_combination = {}
  # print(PackageList)
    #拿到各个实体的packageName,packageCode
    for entity in list_entity:
        if entity.entity_type in ['org','company']:
            #限制附件里角色values[label]最大概率prob
            max_prob = 0.85
            if str(entity.label)!="5" and entity.in_attachment:
                if entity.values[entity.label]>max_prob:
                    entity.values[entity.label] = max_prob
            #过滤掉字数小于3个的实体
            if len(entity.entity_text)<=3:
                continue
            values = entity.values
            role_prob = float(values[int(entity.label)])
            if role_prob>=on_value and str(entity.label)!="5":
                if str(entity.label) in ["0","1"]:
                    packageName = "Project"
                else:
                    if len(PackageSet)>0:
                        packagePointer,_ = getPackage(PackageList,entity.sentence_index,entity.begin_index,"role-"+str(entity.label))
                        if packagePointer is None:
                            #continue
                            packageName = "Project"
                          # print(entity.entity_text, packageName,entity.sentence_index,entity.begin_index)
                        else:
                            #add pointer_pack
                            entity.pointer_pack = packagePointer
                            packageName = packagePointer.entity_text
                          # print(entity.entity_text, packageName)
                    else:
                        packageName = "Project"
                    find_flag = False

                    if packageName in dict_PackageCode.keys():
                        packageCode = dict_PackageCode[packageName]
                    else:
                        packageCode = ""
                    entity.packageCode = packageCode
                role_name = dict_role_id.get(str(entity.label))
                entity.roleName = role_name
                entity.packageName = packageName
                if entity.packageName in dict_role_combination.keys():
                    if str(entity.label) in dict_role_combination[entity.packageName].keys():
                        dict_role_combination[entity.packageName][str(entity.label)].add(entity.entity_text)
                    else:
                        dict_role_combination[entity.packageName][str(entity.label)] = set([entity.entity_text])
                else:
                    dict_role_combination[entity.packageName] = {}
                    #初始化空值
                    roleIds = [0,1,2,3,4]
                    for _roleId in roleIds:
                        dict_role_combination[entity.packageName][str(_roleId)] = set([""])
                    dict_role_combination[entity.packageName][str(entity.label)].add(entity.entity_text)
    list_real_comba = get_legal_comba(list_entity,dict_role_combination)
  # print("===role_combination",dict_role_combination)
  # print("== real_comba",list_real_comba)
    #拿到最大期望值的组合
    max_index = 0
    max_expect = -100
    _index = 0
    dict_pack_entity_prob = get_dict_entity_prob(list_entity)
    for item_combination in list_real_comba:
        expect = getSumExpectation(dict_pack_entity_prob, item_combination)
        if expect>max_expect:
            max_index = _index
            max_expect = expect
        _index += 1
    RoleList = []
    RoleSet = set()
    if len(list_real_comba)>0:
        for _key in list_real_comba[max_index].keys():
            packageName = _key.split("$$")[0]
            label = _key.split("$$")[1]
            role_name = dict_role_id.get(str(label))
            entity_text = list_real_comba[max_index][_key]
            if packageName in dict_PackageCode.keys():
                packagecode = dict_PackageCode.get(packageName)
            else:
                packagecode = ""
            RoleList.append(PREM(packageName,packagecode,role_name,entity_text,0,0,0.0,[]))
            RoleSet.add(entity_text)

    #根据最优树来修正list_entity中角色对包的连接
    for _entity in list_entity:
        if _entity.pointer_pack is not None:
            _pack_name = _entity.pointer_pack.entity_text
            _find_flag = False
            for _prem in RoleList:
                if _prem.packageName==_pack_name and _prem.entity_text==_entity.entity_text:
                    _find_flag = True
            if not _find_flag:
                _entity.pointer_pack = None
    return RoleList,RoleSet,PackageList,PackageSet

def getPackageScopePattern():
    '''
    @summary: 获取包的作用域关键词
    '''
    df = pd.read_excel(os.path.dirname(__file__)+"/end.xls")
    pattern = "("
    for item in df["list_word"]:
        item = str(item).replace("(","\(").replace(")","\)").replace(".","\.").replace("[","\[").replace("]","\]").replace("-","\-")
        pattern += item+"|"
    pattern = pattern[:-1]+")[:：是为]|业绩.{,30}标段[0-9A-Za-z一二三四五六七八九十]{0,3}"
    return pattern
        
pattern_packageScope = getPackageScopePattern()   
def getPackagesFromArticle(list_sentence,list_entity):
    '''
    @param:
        list_sentence:文章的句子list
    @summary: 将包的信息插入list_entity中
    @return: type:list if [包号,句子index,词偏移,标段号] meaning:文章的包/标段信息
    '''
    
    if len(list_sentence)==0:
        return None
    list_sentence.sort(key=lambda x:x.sentence_index)

    PackageList = []
    PackageList_scope = []
    PackageSet = set()
    dict_packageCode = dict()
    
    package_name_pattern = re.compile("((标[段号的包]|分包)的?(名[称单]?|包名))[:：]?([^:：]{3,30}?)，{1}")
    package_N_name_pattern = re.compile("(([^承]|^)分?包|标段|标包|标|包|包组|子项目|包件|项目类型)编?号?[:：]?[\(（]?([0-9A-Za-z一二三四五六七八九十ⅠⅡⅢⅣⅤⅥⅦ]){1,2}，{1}")
    package_number_pattern = re.compile("(((([^承]|^)包|标[段号的包]|分?包|包组|包件)编?号?|子项目|项目类型)[:：]?[0-9A-Za-z一二三四五六七八九十ⅠⅡⅢⅣⅤⅥⅦ]{1,4}[^\.])[^至]?|([^\.]?第[ⅠⅡⅢⅣⅤⅥⅦ0-9A-Za-z一二三四五六七八九十]{1,4}(包号|标[段号的包]|分?包))")  # 第? 去掉问号 修复 纯木浆8包/箱复印 这种作为包号
    # other_package_pattern = re.compile('(项目名称|物资名称|设备名称|场次名称|标段名称)[:：](.{,20}?)(，|项目)')  # 新正则识别标段
    other_package_pattern = re.compile('((项目|物资|设备|场次|标段|标的|产品)(名称)?)[:：]([^，。]{2,50}?)[，。]')  #  # 2020/11/23 大网站规则 调整  package_N_name_pattern， package_N_name_pattern 中的项目 改为 子项目
    win_tenderer_pattern = re.compile('(中标候?选?人|供应商)(名称)?[:：](.{2,25})[，。]')  # 2020/11/23 大网站规则 调整
    model_pattern = re.compile('(型号|序号)[:：]([^，。]{2,20})[，。]')  # 2020/11/23 大网站规则 调整
    number_pattern = re.compile("[0-9A-Za-z一二三四五六七八九十ⅠⅡⅢⅣⅤⅥⅦ]{1,4}")

    package_code_pattern = re.compile("(?:编号[:：]?\s*)([-\dA-Za-z\(\)]+)")
    # 纯数字类型的包号统一，例如：'01','1'
    re_digital = re.compile("^\d+$")
    def changeIndexFromWordToWords(tokens,word_index):
        '''
        @summary:转换某个字的字偏移为词偏移
        '''
        before_index = 0
        after_index = 0
        for i in range(len(tokens)):
            after_index = after_index+len(tokens[i])
            if before_index<=word_index and after_index>=word_index:
                return i
            before_index = after_index
    package_names = []
    
    def extractPackageCode(tokens,word_index,size=20,pattern = package_code_pattern):
        '''
        @summary:抽取包附近的标段号
        @param:
            tokens:包所在句子的分词
            word_index:包所在字偏移
            size:左右各取多少个词
            pattern:提取标段号的正则
        @return: type:string,meaning:标段号
        '''
        index = changeIndexFromWordToWords(tokens,word_index)
        if index<size:
            begin = index
        else:
            begin = index-size
        if index+size>len(tokens):
            end = len(tokens)
        else:
            end = index+size
        #拿到左右两边的词语组成短语
        text = "".join(tokens[begin:end])
        #在短语中的字偏移
        new_word_index = word_index-len("".join(tokens[:begin]))
        min_distance = len(text)
        packageCode = None
        for the_iter in re.finditer(pattern,text):
            #算出最小距离
            distance = min([abs(new_word_index-the_iter.span()[0]),abs(new_word_index-the_iter.span()[1])])
            if distance<min_distance:
                min_distance = distance
                packageCode = the_iter.group(1)
        return packageCode
    #从标段介绍表格中提取包名和包号
    for i in range(len(list_sentence)):
        content = list_sentence[i].sentence_text
        names = re.findall(package_name_pattern,content)
        if names == []:
            names = re.findall(other_package_pattern, content)
        N_names = re.findall(package_N_name_pattern,content)
        if len(names)==1 and len(N_names)==1:
            package_names.append([names[0][-1],N_names[0][-1]])
    for i in range(len(list_sentence)):
        PackageList_item = []
        PackageList_item_scope = []
        content = list_sentence[i].sentence_text
        tokens = list_sentence[i].tokens
        _names = []
        # 2021/6/23 包名称去重
        for name in package_names:
            if name not in _names:
                _names.append(name)
        # for name in package_names[:20]:
        for name in _names[:20]:
            for index in findAllIndex(name[0],content):
                temp_package_number = re.findall(number_pattern,name[1])[0]
                if re.search(re_digital,temp_package_number):
                    temp_package_number = str(int(temp_package_number))
                PackageList_item.append({"name":temp_package_number,"sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,index),"offsetWord_begin":index,"offsetWord_end":index+len(name[0])})
                # PackageList_item.append([temp_package_number,i,changeIndexFromWordToWords(tokens,index),index,index+len(str(temp_package_number))])
                code = extractPackageCode(tokens, index)
                if code is not None:
                    dict_packageCode[temp_package_number] = code
                PackageSet.add(temp_package_number)
        for iter in re.finditer(package_number_pattern,content):
            temp_package_number = re.findall(number_pattern,content[iter.span()[0]:iter.span()[1]])[0]
            if re.search(re_digital, temp_package_number):
                temp_package_number = str(int(temp_package_number))
            PackageList_item.append({"name":temp_package_number,"sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,iter.span()[0]),"offsetWord_begin":iter.span()[0],"offsetWord_end":iter.span()[1]})
            # PackageList_item.append([temp_package_number,i,changeIndexFromWordToWords(tokens,iter.span()[0]),iter.span()[0],iter.span()[1]])
            code = extractPackageCode(tokens, iter.span()[0])
            if code is not None:
                dict_packageCode[temp_package_number] = code
            PackageSet.add(temp_package_number)
        
        #识别packageScope
        for iter in re.finditer(pattern_packageScope,content):
            PackageList_item_scope.append({"name":"","sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,iter.span()[0]),"offsetWord_begin":iter.span()[0],"offsetWord_end":iter.span()[1]})
            # PackageList_item_scope.append(["",i,changeIndexFromWordToWords(tokens,iter.span()[0]),iter.span()[0],iter.span()[1]])
        PackageList_item_scope = PackageList_item +PackageList_item_scope
        PackageList_item_scope.sort(key=lambda x:x["offsetWord_begin"])
        PackageList_scope = PackageList_scope+PackageList_item_scope
        PackageList_item.sort(key=lambda x:x["sentence_index"])
        #PackageList = PackageList+PackageList_item
    #不作为包
    # if len(PackageSet)==0:
    #     for i in range(len(list_sentence)):
    #         PackageList_item = []
    #         PackageList_item_scope = []
    #         content = list_sentence[i].sentence_text
    #         tokens = list_sentence[i].tokens
    #         for iter in re.finditer(other_package_pattern,content):
    #             temp_package_number = iter.group(2)
    #             PackageList_item.append({"name":temp_package_number,"sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,iter.span()[0]),"offsetWord_begin":iter.span()[0],"offsetWord_end":iter.span()[1]})
    #             # PackageList_item.append([temp_package_number,i,changeIndexFromWordToWords(tokens,iter.span()[0]),iter.span()[0],iter.span()[1]])
    #             code = extractPackageCode(tokens, iter.span()[0])
    #             if code is not None:
    #                 dict_packageCode[temp_package_number] = code
    #             PackageSet.add(temp_package_number)
    #         #识别packageScope
    #         for iter in re.finditer(pattern_packageScope,content):
    #             PackageList_item_scope.append({"name":"","sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,iter.span()[0]),"offsetWord_begin":iter.span()[0],"offsetWord_end":iter.span()[1]})
    #             # PackageList_item_scope.append(["",i,changeIndexFromWordToWords(tokens,iter.span()[0]),iter.span()[0],iter.span()[1]])
    #         PackageList_item_scope = PackageList_item +PackageList_item_scope
    #         PackageList_item_scope.sort(key=lambda x:x["offsetWord_begin"])
    #         PackageList_scope = PackageList_scope+PackageList_item_scope
    #         PackageList_item.sort(key=lambda x:x["sentence_index"])

    # 2020/11/23 大网站规则 调整
    if len(PackageSet)==0 and len(set([it.entity_text for it in list_entity if it.entity_type in ['org', 'company'] and it.label==2]))>1:
        for i in range(len(list_sentence)):
            PackageList_item = []
            PackageList_item_scope = []
            content = list_sentence[i].sentence_text
            tokens = list_sentence[i].tokens
            names = re.findall(other_package_pattern, content)
            N_names = re.findall(win_tenderer_pattern, content)
            if len(names) != 1 or len(N_names) != 1:
                continue
            for iter in re.finditer(other_package_pattern,content):
                temp_package_number = iter.group(4)
                xinghao = re.search(model_pattern, content)
                if xinghao:
                    temp_package_number = temp_package_number + '+' + xinghao.group(2)
                # print('新正则采购包名补充',temp_package_number)
                if re.search(re_digital,temp_package_number):
                    temp_package_number = str(int(temp_package_number))
                PackageList_item.append({"name":temp_package_number,"sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,iter.span()[0]),"offsetWord_begin":iter.span()[0],"offsetWord_end":iter.span()[1]})
                # PackageList_item.append([temp_package_number,i,changeIndexFromWordToWords(tokens,iter.span()[0]),iter.span()[0],iter.span()[1]])
                code = extractPackageCode(tokens, iter.span()[0])
                if code is not None:
                    dict_packageCode[temp_package_number] = code
                PackageSet.add(temp_package_number)
            #识别packageScope
            for iter in re.finditer(pattern_packageScope,content):
                PackageList_item_scope.append({"name":"","sentence_index":list_sentence[i].sentence_index,"offsetWords_begin":changeIndexFromWordToWords(tokens,iter.span()[0]),"offsetWord_begin":iter.span()[0],"offsetWord_end":iter.span()[1]})
                # PackageList_item_scope.append(["",i,changeIndexFromWordToWords(tokens,iter.span()[0]),iter.span()[0],iter.span()[1]])
            PackageList_item_scope = PackageList_item +PackageList_item_scope
            PackageList_item_scope.sort(key=lambda x:x["offsetWord_begin"])
            PackageList_scope = PackageList_scope+PackageList_item_scope
            PackageList_item.sort(key=lambda x:x["sentence_index"])
    pattern_punctuation = "[:：（）\(\),，。；;]"
  # print("===packageList_scope",PackageList_scope)
    for i in range(len(list_sentence)):
        for j in range(len(PackageList_scope)):
            if i==PackageList_scope[j]["sentence_index"] and PackageList_scope[j]["name"]!="":
                _flag = False
                left_str = list_sentence[i].sentence_text[PackageList_scope[j]["offsetWord_begin"]-30:PackageList_scope[j]["offsetWord_begin"]+1]
                right_str = list_sentence[i].sentence_text[PackageList_scope[j]["offsetWord_begin"]:PackageList_scope[j]["offsetWord_begin"]+30]
                _left_find = re.findall(pattern_punctuation,left_str)
                _right_find = re.findall(pattern_punctuation,right_str)
                #print(left_str)
                if re.search("同",left_str[-1:]) is not None and PackageList_scope[j]["name"]=="一":
                    continue
                if re.search("划分",right_str[:10]) is not None:
                    continue
                if len(_left_find)>0 and _left_find[-1] in [":","："]:
                    _flag = True
                if len(_right_find)>0 and _right_find[0] in [":","："]:
                    _flag = True
                if _flag:
                    scope_begin = [PackageList_scope[j]["sentence_index"],PackageList_scope[j]["offsetWords_begin"]]
                else:
                    if j==0:
                        scope_begin = [0,0]
                    else:
                        scope_begin = [PackageList_scope[j-1]["sentence_index"],PackageList_scope[j-1]["offsetWords_begin"]]
                if j==len(PackageList_scope)-1:
                    scope_end = [list_sentence[-1].sentence_index,changeIndexFromWordToWords(list_sentence[-1].tokens, len(list_sentence[-1].sentence_text))]
                else:
                    scope_end = [PackageList_scope[j+1]["sentence_index"],PackageList_scope[j+1]["offsetWords_begin"]]
                if PackageList_scope[j-1]["sentence_index"]==PackageList_scope[j]["sentence_index"] and PackageList_scope[j-1]["offsetWord_begin"]<=PackageList_scope[j]["offsetWord_begin"] and PackageList_scope[j-1]["offsetWord_end"]>=PackageList_scope[j]["offsetWord_end"]:
                    continue

                #add package to entity
                _pack_entity = Entity(doc_id=list_sentence[0].doc_id,entity_id="%s_%s_%s_%s"%(list_sentence[0].doc_id,i,PackageList_scope[j]["offsetWord_begin"],PackageList_scope[j]["offsetWord_begin"]),entity_text=PackageList_scope[j]["name"],entity_type="package",sentence_index=PackageList_scope[j]["sentence_index"],begin_index=changeIndexFromWordToWords(list_sentence[i].tokens,PackageList_scope[j]["offsetWord_begin"]),end_index=changeIndexFromWordToWords(list_sentence[i].tokens,PackageList_scope[j]["offsetWord_end"]),wordOffset_begin=PackageList_scope[j]["offsetWord_begin"],wordOffset_end=PackageList_scope[j]["offsetWord_end"],in_attachment=list_sentence[i].in_attachment)
                list_entity.append(_pack_entity)
                copy_pack = copy.copy(PackageList_scope[j])
                copy_pack["scope"] = [scope_begin,scope_end]
                copy_pack["hit"] = set()
                copy_pack["pointer"] = _pack_entity

                PackageList.append(copy_pack)
    return PackageList,PackageSet,dict_packageCode

# km配对方法
def dispatch(match_list):
    main_roles = list(set([match.main_role for match in match_list]))
    attributes = list(set([match.attribute for match in match_list]))

    label = np.zeros(shape=(len(main_roles), len(attributes)))
    for match in match_list:
        main_role = match.main_role
        attribute = match.attribute
        value = match.value
        label[main_roles.index(main_role), attributes.index(attribute)] = value + 10000
    # print(label)
    gragh = -label
    # km算法
    row, col = linear_sum_assignment(gragh)
    max_dispatch = [(i, j) for i, j, value in zip(row, col, gragh[row, col]) if value]
    # return [Match(main_roles[row], attributes[col]) for row, col in max_dispatch]
    return [(main_roles[row], attributes[col]) for row, col in max_dispatch]

from BiddingKG.dl.common.Utils import getUnifyMoney
from BiddingKG.dl.interface.modelFactory import Model_relation_extraction
relationExtraction_model = Model_relation_extraction()
def findAttributeAfterEntity(PackDict,roleSet,PackageList,PackageSet,list_sentence,list_entity,list_outline,on_value = 0.5,on_value_person=0.5,sentence_len=4):
    '''
    @param:
        PackDict:文章包dict
        roleSet:文章所有角色的公司名称
        PackageList:文章的包信息
        PackageSet:文章所有包的名称
        list_entity:文章所有经过模型处理的实体
        on_value:金额模型的阈值
        on_value_person:联系人模型的阈值
        sentence_len:公司和属性间隔句子的最大长度
    @return:添加了属性信息的角色list
    '''
    
    #根据roleid添加金额到rolelist中
    def addMoneyByRoleid(packDict,packageName,roleid,money,money_prob):
        for i in range(len(packDict[packageName]["roleList"])):
            if packDict[packageName]["roleList"][i].role_name==dict_role_id.get(str(roleid)):
                if money_prob>packDict[packageName]["roleList"][i].money_prob:
                    packDict[packageName]["roleList"][i].money = money
                    packDict[packageName]["roleList"][i].money_prob = money_prob
        return packDict
                    
    #根据实体名称添加金额到rolelist中
    def addMoneyByEntity(packDict,packageName,entity,money,money_prob):
        for i in range(len(packDict[packageName]["roleList"])):
            if packDict[packageName]["roleList"][i].entity_text==entity:
                # if money_prob>packDict[packageName]["roleList"][i].money_prob:
                #     packDict[packageName]["roleList"][i].money = money
                #     packDict[packageName]["roleList"][i].money_prob = money_prob
                if packDict[packageName]["roleList"][i].money_prob==0 :  # 2021/7/20第一次更新金额
                    packDict[packageName]["roleList"][i].money = money.entity_text
                    packDict[packageName]["roleList"][i].money_prob = money_prob
                    packDict[packageName]["roleList"][i].money_unit = money.money_unit
                elif money_prob>packDict[packageName]["roleList"][i].money_prob+0.2 or money.notes in ['大写']: # 2021/7/20改为优先选择大写金额,
                    # print('已连接金额概率：money_prob:',packDict[packageName]["roleList"][i].money_prob)
                    # print('链接金额备注 ',money.notes, money.entity_text, money.values)
                    packDict[packageName]["roleList"][i].money = money.entity_text
                    packDict[packageName]["roleList"][i].money_prob = money_prob
                    packDict[packageName]["roleList"][i].money_unit = money.money_unit
                # print('链接中的金额：{0}, 单位：{1}'.format(money.entity_text, money.money_unit))
        return packDict
    def addRatioByEntity(packDict,packageName,entity,ratio):
        for i in range(len(packDict[packageName]["roleList"])):
            if packDict[packageName]["roleList"][i].entity_text==entity:
                packDict[packageName]["roleList"][i].ratio = ratio.entity_text
    def addServiceTimeByEntity(packDict,packageName,entity,serviceTime):
        for i in range(len(packDict[packageName]["roleList"])):
            if packDict[packageName]["roleList"][i].entity_text==entity:
                packDict[packageName]["roleList"][i].serviceTime = serviceTime.entity_text

    #根据实体名称得到角色
    def getRoleWithText(packDict,entity_text):
        for pack in packDict.keys():
            for i in range(len(packDict[pack]["roleList"])):
                if packDict[pack]["roleList"][i].entity_text==entity_text:
                    return packDict[pack]["roleList"][i].role_name
    
    def doesEntityOrLinkedEntity_inRoleSet(entity,RoleSet):
        _list_entitys = [entity]+entity.linked_entitys
        for _entity in _list_entitys:
            if _entity.entity_text in RoleSet:
                return True
    
    p_entity = 0

    # 2021/7/19 顺序比较金额，前面是后面的一万倍则把前面金额/10000
    money_list = [it for it in list_entity if it.entity_type=="money"]
    for i in range(len(money_list)-1):
        for j in range(1, len(money_list)):
            if (float(money_list[i].entity_text) > 5000000000 or money_list[j].notes=='大写') and \
                    Decimal(money_list[i].entity_text)/Decimal(money_list[j].entity_text)==10000:
                money_list[i].entity_text = str(Decimal(money_list[i].entity_text)/10000)
                # print('连接前修改大于50亿金额：前面是后面的一万倍则把前面金额/10000')
    
    #遍历所有实体
    # while(p_entity<len(list_entity)):
    #     entity = list_entity[p_entity]
        '''
        #招标金额从后往前找
        if entity.entity_type=="money":
            if entity.values[entity.label]>=on_value:
                if str(entity.label)=="0":
                    packagePointer,_ = getPackage(PackageList,entity.sentence_index,entity.begin_index,"money-"+str(entity.label))
                    if packagePointer is None:
                        packageName = "Project"
                    else:
                        packageName = packagePointer.entity_text
                    addMoneyByRoleid(PackDict, packageName, "0", entity.entity_text, entity.values[entity.label])
        '''
        ''' # 2020/11/25 与下面的联系人连接步骤重复，取消
        if entity.entity_type=="person":
            if entity.values[entity.label]>=on_value_person:
                if str(entity.label)=="1":
                    for i in range(len(PackDict["Project"]["roleList"])):
                        if PackDict["Project"]["roleList"][i].role_name=="tenderee":
                            PackDict["Project"]["roleList"][i].linklist.append((entity.entity_text,entity.person_phone))
                        # add pointer_person
                        for _entity in list_entity:
                            if dict_role_id.get(str(_entity.label))=="tenderee":
                                for i in range(len(PackDict["Project"]["roleList"])):
                                    if PackDict["Project"]["roleList"][i].entity_text==_entity.entity_text and PackDict["Project"]["roleList"][i].role_name=="tenderee":
                                        _entity.pointer_person = entity
                elif str(entity.label)=="2":
                    for i in range(len(PackDict["Project"]["roleList"])):
                        if PackDict["Project"]["roleList"][i].role_name=="agency":
                            PackDict["Project"]["roleList"][i].linklist.append((entity.entity_text,entity.person_phone))
                    # add pointer_person
                    for _entity in list_entity:
                        if dict_role_id.get(str(_entity.label))=="agency":
                            for i in range(len(PackDict["Project"]["roleList"])):
                                if PackDict["Project"]["roleList"][i].entity_text==_entity.entity_text and PackDict["Project"]["roleList"][i].role_name=="agency":
                                    _entity.pointer_person = entity
    '''
        # #金额往前找实体
        # if entity.entity_type=="money":
        #     if entity.values[entity.label]>=on_value:
        #         p_entity_money= p_entity
        #         entity_money = list_entity[p_entity_money]
        #         if len(PackageSet)>0:
        #             packagePointer,_ = getPackage(PackageList,entity_money.sentence_index,entity_money.begin_index,"money-"+str(entity_money.entity_text)+"-"+str(entity_money.label))
        #             if packagePointer is None:
        #                 packageName_entity = "Project"
        #             else:
        #                 packageName_entity = packagePointer.entity_text
        #         else:
        #             packageName_entity = "Project"
        #         while(p_entity_money>0):
        #             entity_before = list_entity[p_entity_money]
        #             if entity_before.entity_type in ['org','company']:
        #                 if str(entity_before.label)=="1":
        #                     addMoneyByEntity(PackDict, packageName_entity, entity_before.entity_text, entity_money.entity_text, entity_money.values[entity_money.label])
        #                     #add pointer_money
        #                     entity_before.pointer_money = entity_money
        #                 break
        #             p_entity_money -= 1



        #如果实体属于角色集合，则往后找属性
        # if doesEntityOrLinkedEntity_inRoleSet(entity, roleSet):
        #
        #     p_entity += 1
        #     #循环查找符合的属性
        #     while(p_entity<len(list_entity)):
        #
        #         entity_after = list_entity[p_entity]
        #         if entity_after.sentence_index-entity.sentence_index>=sentence_len:
        #             p_entity -= 1
        #             break
        #         #若是遇到公司实体，则跳出循环
        #         if entity_after.entity_type in ['org','company']:
        #             p_entity -= 1
        #             break
        #         if entity_after.values is not None:
        #             if entity_after.entity_type=="money":
        #                 if entity_after.values[entity_after.label]>=on_value:
        #                     '''
        #                     #招标金额从后往前找
        #                     if str(entity_after.label)=="0":
        #                         packagePointer,_ = getPackage(PackageList,entity.sentence_index,entity.begin_index,"money-"+str(entity.label))
        #                         if packagePointer is None:
        #                             packageName = "Project"
        #                         else:
        #                             packageName = packagePointer.entity_text
        #                         addMoneyByRoleid(PackDict, packageName, "0", entity_after.entity_text, entity_after.values[entity_after.label])
        #                     '''
        #                     if str(entity_after.label)=="1":
        #                         #print(entity_after.entity_text,entity.entity_text)
        #                         _list_entitys = [entity]+entity.linked_entitys
        #                         if len(PackageSet)>0:
        #                             packagePointer,_ = getPackage(PackageList,entity_after.sentence_index,entity_after.begin_index,"money-"+str(entity_after.entity_text)+"-"+str(entity_after.label))
        #                             if packagePointer is None:
        #                                 packageName_entity = "Project"
        #                             else:
        #                                 packageName_entity = packagePointer.entity_text
        #                         else:
        #                             packageName_entity = "Project"
        #                         if str(entity.label) in ["2","3","4"]:
        #                             # addMoneyByEntity(PackDict, packageName_entity, entity.entity_text, entity_after.entity_text, entity_after.values[entity_after.label])
        #                             if entity_after.notes == '单价' or float(entity_after.entity_text)<5000: #2021/12/17 调整小金额阈值，避免203608823.html 两次金额一次万元没提取到的情况
        #                                 addMoneyByEntity(PackDict, packageName_entity, entity.entity_text, entity_after,
        #                                                  0.5)
        #                                 entity.pointer_money = entity_after
        #                                 # print('role zhao money', entity.entity_text, '中标金额：', entity_after.entity_text)
        #                             else:
        #                                 addMoneyByEntity(PackDict, packageName_entity, entity.entity_text, entity_after,
        #                                                  entity_after.values[entity_after.label])
        #                                 entity.pointer_money = entity_after
        #                                 # print('role zhao money', entity.entity_text, '中标金额：', entity_after.entity_text)
        #                                 if entity_after.values[entity_after.label]>0.6:
        #                                     break # 2021/7/16 新增，找到中标金额，非单价即停止，不再往后找金额
        #                             #add pointer_money
        #                             # entity.pointer_money = entity_after
        #                             # print('role zhao money', entity.entity_text, '中标金额：', entity_after.entity_text)
        #                             # if entity_after.notes!='单价':
        #                             #     break  # 2021/7/16 新增，找到中标金额即停止，不再往后找金额
        #                 '''
        #             if entity_after.entity_type=="person":
        #                 if entity_after.values[entity_after.label]>=on_value_person:
        #                     if str(entity_after.label)=="1":
        #                         for i in range(len(roleList)):
        #                             if roleList[i].role_name=="tenderee":
        #                                 roleList[i].linklist.append((entity_after.entity_text,entity_after.person_phone))
        #                     elif str(entity_after.label)=="2":
        #                         for i in range(len(roleList)):
        #                             if roleList[i].role_name=="agency":
        #                                 roleList[i].linklist.append((entity_after.entity_text,entity_after.person_phone))
        #                     elif str(entity_after.label)=="3":
        #                         _list_entitys = [entity]+entity.linked_entitys
        #                         for _entity in _list_entitys:
        #                             for i in range(len(roleList)):
        #                                 if roleList[i].entity_text==_entity.entity_text:
        #                                     if entity_after.sentence_index-_entity.sentence_index>1 and len(roleList[i].linklist)>0:
        #                                         break
        #                                     roleList[i].linklist.append((entity_after.entity_text,entity_after.person_phone))
        #             '''
        #
        #         p_entity += 1
        #
        # p_entity += 1
    # 记录每句的分词数量
    tokens_num_dict = dict()
    last_tokens_num = 0
    for sentence in list_sentence:
        _index = sentence.sentence_index
        if _index == 0:
            tokens_num_dict[_index] = 0
        else:
            tokens_num_dict[_index] = tokens_num_dict[_index - 1] + last_tokens_num
        last_tokens_num = len(sentence.tokens)
    attribute_type = ['money','serviceTime','ratio']# 'money'仅指“中投标金额”
    for link_attribute in attribute_type:
        temp_entity_list = []
        if link_attribute=="money":
            temp_entity_list = [ent for ent in list_entity if (ent.entity_type in ['org','company'] and ent.label in [2,3,4]) or
                                (ent.entity_type=='money' and ent.label==1 and ent.values[ent.label]>=0.5)]
            # 删除重复的‘中投标金额’，一般为大小写两种样式
            drop_tendererMoney = []
            for ent_idx in range(len(temp_entity_list)-1):
                entity = temp_entity_list[ent_idx]
                if entity.entity_type=='money':
                    next_entity = temp_entity_list[ent_idx+1]
                    if next_entity.entity_type=='money':
                        if getUnifyMoney(entity.entity_text)==getUnifyMoney(next_entity.entity_text):
                            if (tokens_num_dict[next_entity.sentence_index] + next_entity.begin_index) - (
                                               tokens_num_dict[entity.sentence_index] + entity.end_index) < 10:
                                drop_tendererMoney.append(next_entity)
            for _drop in drop_tendererMoney:
                temp_entity_list.remove(_drop)
        elif link_attribute=="serviceTime":
            temp_entity_list = [ent for ent in list_entity if (ent.entity_type in ['org','company'] and ent.label in [2,3,4]) or
                                ent.entity_type=='serviceTime']
        elif link_attribute=="ratio":
            temp_entity_list = [ent for ent in list_entity if (ent.entity_type in ['org','company'] and ent.label in [2,3,4]) or
                                ent.entity_type=='ratio']
        temp_entity_list = sorted(temp_entity_list,key=lambda x: (x.sentence_index, x.begin_index))
        temp_match_list = []
        for ent_idx in range(len(temp_entity_list)):
            entity = temp_entity_list[ent_idx]
            if entity.entity_type in ['org','company']:
                match_nums = 0
                tenderer_nums = 0 #经过其他中投标人的数量
                byNotTenderer_match_nums = 0 #跟在中投标人后面的属性
                for after_index in range(ent_idx + 1, min(len(temp_entity_list), ent_idx + 4)):
                    after_entity = temp_entity_list[after_index]
                    if after_entity.entity_type == link_attribute:
                        distance = (tokens_num_dict[after_entity.sentence_index] + after_entity.begin_index) - (
                                           tokens_num_dict[entity.sentence_index] + entity.end_index)
                        sentence_distance = after_entity.sentence_index - entity.sentence_index
                        value = (-1 / 2 * (distance ** 2)) / 10000
                        if link_attribute == "money":
                            if after_entity.notes == '单价':
                                value = value * 100
                        if sentence_distance == 0:
                            if distance < 100:
                                # value = (-1 / 2 * (distance ** 2)) / 10000
                                temp_match_list.append(Match(entity, after_entity, value))
                                match_nums += 1
                                if not tenderer_nums:
                                    byNotTenderer_match_nums += 1
                                else:
                                    break
                        else:
                            if distance < 60:
                                # value = (-1 / 2 * (distance ** 2)) / 10000
                                temp_match_list.append(Match(entity, after_entity, value))
                                match_nums += 1
                                if not tenderer_nums:
                                    byNotTenderer_match_nums += 1
                                else:
                                    break
                    else:
                        tenderer_nums += 1
                #前向查找属性
                if ent_idx!=0 and (not match_nums or not byNotTenderer_match_nums):
                    previous_entity = temp_entity_list[ent_idx - 1]
                    if previous_entity.entity_type == link_attribute:
                        # if previous_entity.sentence_index == entity.sentence_index:
                        distance = (tokens_num_dict[entity.sentence_index] + entity.begin_index) - (
                                tokens_num_dict[previous_entity.sentence_index] + previous_entity.end_index)
                        if distance < 40:
                            # 前向 没有 /10000
                            value = (-1 / 2 * (distance ** 2))
                            temp_match_list.append(Match(entity, previous_entity, value))
        # km算法分配求解
        dispatch_result = dispatch(temp_match_list)
        dispatch_result = sorted(dispatch_result, key=lambda x: (x[0].sentence_index,x[0].begin_index))
        for match in dispatch_result:
            _entity = match[0]
            _attribute = match[1]
            if link_attribute=='money':
                _entity.pointer_money = _attribute
                packagePointer, _ = getPackage(PackageList, _attribute.sentence_index, _attribute.begin_index,
                                               "money-" + str(_attribute.entity_text) + "-" + str(_attribute.label))
                # print(_entity.entity_text,_attribute.entity_text)
                if packagePointer is None:
                    packageName_entity = "Project"
                else:
                    packageName_entity = packagePointer.entity_text
                if _attribute.notes == '单价' or float(_attribute.entity_text) < 5000:  # 2021/12/17 调整小金额阈值，避免203608823.html 两次金额一次万元没提取到的情况
                    # print(packageName_entity,_attribute.entity_text, _attribute.values[_attribute.label])
                    addMoneyByEntity(PackDict, packageName_entity, _entity.entity_text, _attribute,0.5)
                else:
                    # print(packageName_entity,_attribute.entity_text, _attribute.values[_attribute.label])
                    addMoneyByEntity(PackDict, packageName_entity, _entity.entity_text, _attribute,
                                     _attribute.values[_attribute.label])
            elif link_attribute=='serviceTime':
                _entity.pointer_serviceTime = _attribute
                packagePointer, _ = getPackage(PackageList, _attribute.sentence_index, _attribute.begin_index,
                                               "serviceTime-" + str(_attribute.entity_text) + "-" + str(_attribute.label))
                if packagePointer is None:
                    packageName_entity = "Project"
                else:
                    packageName_entity = packagePointer.entity_text
                addServiceTimeByEntity(PackDict, packageName_entity, _entity.entity_text, _attribute)
            elif link_attribute=='ratio':
                _entity.pointer_ratio = _attribute
                packagePointer, _ = getPackage(PackageList, _attribute.sentence_index, _attribute.begin_index,
                                               "ratio-" + str(_attribute.entity_text) + "-" + str(_attribute.label))
                if packagePointer is None:
                    packageName_entity = "Project"
                else:
                    packageName_entity = packagePointer.entity_text
                addRatioByEntity(PackDict, packageName_entity, _entity.entity_text, _attribute)

    ''''''
    # 通过模型分类的招标/代理联系人
    list_sentence = sorted(list_sentence, key=lambda x: x.sentence_index)
    person_list = [entity for entity in list_entity if entity.entity_type == 'person' and entity.label in [1, 2]]
    tenderee_contact = set()
    tenderee_phone = set()
    agency_contact = set()
    agency_phone = set()
    winter_contact = set()
    for _person in person_list:
        if _person.label == 1:
            tenderee_contact.add(_person.entity_text)
        if _person.label == 2:
            agency_contact.add(_person.entity_text)
    # 正则匹配无 '主体/联系人' 的电话
    # 例："采购人联系方式：0833-5226788，"
    phone_pattern = '(1[3-9][0-9][-—－―]?\d{4}[-—－―]?\d{4}|' \
                    '\+86.?1[3-9]\d{9}|' \
                    '0[1-9]\d{1,2}[-—－―][1-9]\d{6,7}/[1-9]\d{6,10}|' \
                    '0[1-9]\d{1,2}[-—－―]\d{7,8}.?转\d{1,4}|' \
                    '0[1-9]\d{1,2}[-—－―]\d{7,8}[-—－―]\d{1,4}|' \
                    '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=1[3-9]\d{9})|' \
                   '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?)|' \
                   '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=[1-9]\d{6,7})|' \
                   '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?|' \
                   '[\（|\(]0[1-9]\d{1,2}[\）|\)]-?\d{7,8}-?\d{,4}|' \
                   '[2-9]\d{6,7})'
    re_tenderee_phone = re.compile(
        "(?:(?:(?:采购|招标|议价|议标|比选)(?:人|公司|单位|组织|部门)|建设(?:单位|业主)|(?:采购|招标|甲)方|询价单位|项目业主|业主)[^。]{0,5}(?:电话|联系方式|联系人|联系电话)[:：]?[^。]{0,7}?)"
        # 电话号码
        + phone_pattern)
    # 例："采购人地址和联系方式：峨边彝族自治县教育局，0833-5226788，"
    re_tenderee_phone2 = re.compile(
        "(?:(?:(?:采购|招标|议价|议标|比选)(?:人|公司|单位|组织|部门)|建设(?:单位|业主)|(?:采购|招标|甲)方|询价单位|项目业主|业主)[^。]{0,3}(?:地址)[^。]{0,3}(?:电话|联系方式|联系人|联系电话)[:：]?[^。]{0,20}?)"
        # 电话号码
        + phone_pattern)
    re_agent_phone = re.compile(
        "(?:(?:代理(?:人|机构|公司|单位|组织|方)|采购机构|集中采购机构|集采机构|招标机构)[^。]{0,5}(?:电话|联系方式|联系人|联系电话)[:：]?[^。]{0,7}?)"
        # 电话号码
        + phone_pattern)
    re_agent_phone2 = re.compile(
        "(?:(?:代理(?:人|机构|公司|单位|组织|方)|采购机构|集中采购机构|集采机构|招标机构)[^。]{0,3}(?:地址)[^。]{0,3}(?:电话|联系方式|联系人|联系电话)[:：]?[^。]{0,20}?)"
        # 电话号码
        + phone_pattern)
    content = ""
    for _sentence in list_sentence:
        content += "".join(_sentence.tokens)
    _content = copy.deepcopy(content)
    while re.search("(.)(，)([^0-9])|([^0-9])(，)(.)", content):
        content_words = list(content)
        for i in re.finditer("(.)(，)([^0-9])", content):
            content_words[i.span(2)[0]] = ""
        for i in re.finditer("([^0-9])(，)(.)", content):
            content_words[i.span(2)[0]] = ""
        content = "".join(content_words)
    content = re.sub("[:：]|[\(（]|[\)）]", "", content)
    _tenderee_phone = re.findall(re_tenderee_phone, content)
    # 更新正则确定的角色属性
    for i in range(len(PackDict["Project"]["roleList"])):
        if PackDict["Project"]["roleList"][i].role_name == "tenderee":
            _tenderee_phone = re.findall(re_tenderee_phone, content)
            if _tenderee_phone:
                for _phone in _tenderee_phone:
                    _phone = _phone.split("/") # 分割多个号码
                    for one_phone in _phone:
                        PackDict["Project"]["roleList"][i].linklist.append(("", one_phone))
                        tenderee_phone.add(one_phone)
            _tenderee_phone2 = re.findall(re_tenderee_phone2, content)
            if _tenderee_phone2:
                for _phone in _tenderee_phone2:
                    _phone = _phone.split("/")
                    for one_phone in _phone:
                        PackDict["Project"]["roleList"][i].linklist.append(("", one_phone))
                        tenderee_phone.add(one_phone)
        if PackDict["Project"]["roleList"][i].role_name == "agency":
            _agent_phone = re.findall(re_agent_phone, content)
            if _agent_phone:
                for _phone in _agent_phone:
                    _phone = _phone.split("/")
                    for one_phone in _phone:
                        PackDict["Project"]["roleList"][i].linklist.append(("", one_phone))
                        agency_phone.add(one_phone)
            _agent_phone2 = re.findall(re_agent_phone2, content)
            if _agent_phone2:
                for _phone in _agent_phone2:
                    _phone = _phone.split("/")
                    for one_phone in _phone:
                        PackDict["Project"]["roleList"][i].linklist.append(("", one_phone))
                        agency_phone.add(one_phone)

    # 正则提取电话号码实体
    # key_word = re.compile('((?:电话|联系方式|联系人).{0,4}?)([0-1]\d{6,11})')
    phone = re.compile('1[3-9][0-9][-—－―]?\d{4}[-—－―]?\d{4}|'
                       '\+86.?1[3-9]\d{9}|'
                       # '0[^0]\d{1,2}[-—－―][1-9]\d{6,7}/[1-9]\d{6,10}|'
                       '0[1-9]\d{1,2}[-—－―]\d{7,8}.?转\d{1,4}|'
                       '0[1-9]\d{1,2}[-—－―]\d{7,8}[-—－―]\d{1,4}|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=1[3-9]\d{9})|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?)|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=[1-9]\d{6,7})|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?|'
                       '[\（|\(]0[1-9]\d{1,2}[\）|\)]-?\d{7,8}-?\d{,4}|'
                       '[2-9]\d{6,7}')
    url_pattern = re.compile("http[s]?://(?:[a-zA-Z]|[0-9]|[$\-_@.&+=\?:/]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+")
    email_pattern = re.compile("[a-zA-Z0-9][a-zA-Z0-9_-]+(?:\.[a-zA-Z0-9_-]+)*@"
                            "[a-zA-Z0-9_-]+(?:\.[a-zA-Z0-9_-]+)*(?:\.[a-zA-Z]{2,})")
    phone_entitys = []
    code_entitys = [ent for ent in list_entity if ent.entity_type=='code']
    for _sentence in list_sentence:
        sentence_text = _sentence.sentence_text
        in_attachment = _sentence.in_attachment
        list_tokenbegin = []
        begin = 0
        for i in range(0, len(_sentence.tokens)):
            list_tokenbegin.append(begin)
            begin += len(str(_sentence.tokens[i]))
        list_tokenbegin.append(begin + 1)
        # 排除网址、邮箱、项目编号实体
        error_list = []
        for i in re.finditer(url_pattern, sentence_text):
            error_list.append((i.start(), i.end()))
        for i in re.finditer(email_pattern, sentence_text):
            error_list.append((i.start(), i.end()))
        for code_ent in [ent for ent in code_entitys if ent.sentence_index==_sentence.sentence_index]:
            error_list.append((code_ent.wordOffset_begin,code_ent.wordOffset_end))
        res_set = set()
        for i in re.finditer(phone, sentence_text):
            is_continue = False
            for error_ent in error_list:
                if i.start()>=error_ent[0] and i.end()<=error_ent[1]:
                    is_continue = True
                    break
            if is_continue:
                continue
            res_set.add((i.group(), i.start(), i.end()))
        res_set = sorted(list(res_set),key=lambda x:x[1])
        last_phone_mask = True
        for item_idx in range(len(res_set)):
            item = res_set[item_idx]
            phone_left = sentence_text[max(0, item[1] - 10):item[1]]
            phone_right = sentence_text[item[2]:item[2] + 8]
            if re.search("电话|手机|联系人|联系方式”",re.sub("，","",phone_left)):
                pass
            else:
                # 排除“传真号”和其它错误项
                if re.search("传，?真|信，?箱|邮，?[箱件]|QQ|qq", phone_left):
                    if not re.search("电，?话", phone_left):
                        last_phone_mask = False
                        continue
                if re.search("注册[证号]|帐号|编[号码]|报价|标价|证号|价格|型号|附件|代码|列号|行号|税号|[\(\（]万?元[\)\）]|[a-zA-Z]+\d*$", re.sub("，","",phone_left)):
                    last_phone_mask = False
                    continue
                if re.search("^\d{0,4}[.,]\d{2,}|^[0-9a-zA-Z\.]*@|^\d*[a-zA-Z]+|元", phone_right):
                    last_phone_mask = False
                    continue
                # 前后跟着字母
                if re.search("[a-zA-Z/]+$", phone_left) or re.search("^[a-zA-Z/]+", phone_right):
                    last_phone_mask = False
                    continue
                # 前后跟着长度小于一定值数字的正则排除
                if re.search("\d+[-—－―]?\d*$",phone_left) or re.search("^\d+[-—－―]?\d*",phone_right):
                    phone_left_number = re.search("\d+[-—－―]?\d*$",phone_left)
                    phone_right_number = re.search("^\d+[-—－―]?\d+",phone_right)
                    if phone_left_number:
                        if len(phone_left_number.group())<7:
                            last_phone_mask = False
                            continue
                    if phone_right_number:
                        if len(phone_right_number.group())<7:
                            last_phone_mask = False
                            continue
                # if:上一个phone实体不符合条件
                if not last_phone_mask:
                    item_start = item[1]
                    last_item_end = res_set[item_idx-1][2]
                    if item_start - last_item_end<=1 or re.search("^[\da-zA-Z\-—－―、]+$",sentence_text[last_item_end:item_start]):
                        last_phone_mask = False
                        continue
            for j in range(len(list_tokenbegin)):
                if list_tokenbegin[j] == item[1]:
                    begin_index = j
                    break
                elif list_tokenbegin[j] > item[1]:
                    begin_index = j - 1
                    break
            for j in range(begin_index, len(list_tokenbegin)):
                if list_tokenbegin[j] >= item[2]:
                    end_index = j - 1
                    break
            _entity = Entity(_sentence.doc_id, None, item[0], "phone", _sentence.sentence_index, begin_index, end_index, item[1],
                             item[2],in_attachment=in_attachment)
            phone_entitys.append(_entity)
            last_phone_mask = True

    def is_company(entity,text):
        # 判断"公司"实体是否为地址地点
        if entity.label!=5 and entity.values[entity.label]>0.5:
            return True
        if ent.is_tail==True:
            return False
        entity_left = text[max(0,entity.wordOffset_begin-10):entity.wordOffset_begin]
        entity_left = re.sub("，（）\(\)","",entity_left)
        entity_left = entity_left[-5:]
        if re.search("地址|地点|银行[：:]",entity_left):
            return False
        else:
            return True
    pre_entity = []
    for ent in list_entity:
        if (ent.entity_type in ['company','org','phone'] and is_company(ent,list_sentence[ent.sentence_index].sentence_text)) or (ent.entity_type=='person' and ent.label in [1,2,3]) \
                or (ent.entity_type=='location' and len(ent.entity_text)>5):
            pre_entity.append(ent)
    text_data,pre_data = relationExtraction_model.encode(pre_entity + phone_entitys, list_sentence)
    # print(pre_data)
    maxlen = 512
    relation_list = []
    if 0<len(text_data)<=maxlen:
        relation_list = relationExtraction_model.predict(text_data, pre_data)
    else:
        # 公告大于maxlen时，分段预测
        start = 0
        # print("len(pre_data)",len(pre_data))
        temp_data = []
        deal_data = 0
        while start<len(pre_data):
            _pre_data = pre_data[start:start+maxlen]
            _text_data = text_data[start:start+maxlen]
            if relationExtraction_model.check_data(_pre_data):
                temp_data.append((_text_data,_pre_data))
            else:
                if temp_data:
                    deal_data += len(temp_data)
                    if deal_data>3:
                        break
                    for _text_data, _pre_data in temp_data:
                        relation_list.extend(relationExtraction_model.predict(_text_data,_pre_data))
                    temp_data = []
            start = start + maxlen - 120
        # print("预测数据：",len(temp_data))
        # if len(temp_data)<=6:
        #     for _text_data,_pre_data in temp_data:
        #         relation_list.extend(relationExtraction_model.predict(_text_data,_pre_data))
        # else:
        #     relation_list = []
        # 去重结果
        relation_list = list(set(relation_list))
    # print(relation_list)
    # tokens_num_dict = dict()
    # last_tokens_num = 0
    # for sentence in list_sentence:
    #     _index = sentence.sentence_index
    #     if _index == 0:
    #         tokens_num_dict[_index] = 0
    #     else:
    #         tokens_num_dict[_index] = tokens_num_dict[_index - 1] + last_tokens_num
    #     last_tokens_num = len(sentence.tokens)
    right_combination = [('org','person'),('company','person'),('company','location'),('org','location'),('person','phone')]
    linked_company = set()
    linked_person = set()
    linked_connetPerson = set()
    linked_phone = set()
    for predicate in ["rel_address","rel_phone","rel_person"]:
        _match_list = []
        _match_combo = []
        for relation in relation_list:
            _subject = relation[0]
            _object = relation[2]
            if isinstance(_subject,Entity) and isinstance(_object,Entity) and (_subject.entity_type,_object.entity_type) in right_combination:
                if relation[1]==predicate:
                    if predicate=="rel_person":
                        if (_subject.label==0 and _object.entity_text in agency_contact ) or (_subject.label==1 and _object.entity_text in tenderee_contact):
                            continue
                    distance = (tokens_num_dict[_object.sentence_index] + _object.begin_index) - (
                                tokens_num_dict[_subject.sentence_index] + _subject.end_index)
                    if distance>0:
                        value = (-1 / 2 * (distance ** 2))/10000
                    else:
                        distance = abs(distance)
                        value = (-1 / 2 * (distance ** 2))
                    _match_list.append(Match(_subject,_object,value))
                    _match_combo.append((_subject,_object))
        match_result = dispatch(_match_list)
        error_list = []
        for mat in list(set(_match_combo)-set(match_result)):
            for temp in match_result:
                if mat[1]==temp[1] and mat[0]!=temp[0]:
                    error_list.append(mat)
                    break
        result = list(set(_match_combo)-set(error_list))
        if predicate=='rel_person':
            # 从后往前更新状态，已近后向链接的属性不在前向链接（解决错误链接）
            result = sorted(result,key=lambda x:x[1].begin_index,reverse=True)
            for combo in result:
                is_continue = False
                if not combo[0].pointer_person:
                    combo[0].pointer_person = []
                if combo[1].begin_index<combo[0].begin_index:
                    if combo[0].pointer_person:
                        for temp in combo[0].pointer_person:
                            if temp.begin_index>combo[0].begin_index:
                                is_continue = True
                                break
                if is_continue: continue
                combo[0].pointer_person.append(combo[1])
                linked_company.add(combo[0])
                linked_person.add(combo[1])
                # print(1,combo[0].entity_text,combo[1].entity_text)
        if predicate=='rel_address':
            result = sorted(result,key=lambda x:x[1].begin_index,reverse=True)
            for combo in result:
                if combo[0].pointer_address:
                    continue
                combo[0].pointer_address = combo[1]
                # print(2,combo[0].entity_text,combo[1].entity_text)
        if predicate=='rel_phone':
            result = sorted(result,key=lambda x:x[1].begin_index,reverse=True)
            for combo in result:
                is_continue = False
                if not combo[0].person_phone:
                    combo[0].person_phone = []
                if combo[1].begin_index<combo[0].begin_index:
                    if combo[0].person_phone:
                        for temp in combo[0].person_phone:
                            if temp.begin_index>combo[0].begin_index:
                                is_continue = True
                                break
                if is_continue: continue
                combo[0].person_phone.append(combo[1])
                linked_connetPerson.add(combo[0])
                linked_phone.add(combo[1])
                if combo[0].label in [1,2]:
                    if PackDict.get("Project"):
                        for i in range(len(PackDict["Project"]["roleList"])):
                            if (combo[0].label==1 and PackDict["Project"]["roleList"][i].role_name=='tenderee') \
                                    or (combo[0].label==2 and PackDict["Project"]["roleList"][i].role_name=='agency'):
                                PackDict["Project"]["roleList"][i].linklist.append((combo[0].entity_text,combo[1].entity_text))
                                break
                # print(3,combo[0].entity_text,combo[1].entity_text)
    # "联系人——联系电话" 链接规则补充
    person_phone_EntityList = [ent for ent in pre_entity+ phone_entitys if ent.entity_type not in ['company','org','location']]
    person_phone_EntityList = sorted(person_phone_EntityList, key=lambda x: (x.sentence_index, x.begin_index))
    t_match_list = []
    for ent_idx in range(len(person_phone_EntityList)):
        entity = person_phone_EntityList[ent_idx]
        if entity.entity_type=="person":
            match_nums = 0
            person_nums = 0  # 经过其他中联系人的数量
            byNotPerson_match_nums = 0  # 跟在联系人后面的属性
            phone_nums = 0 # 经过电话的数量
            for after_index in range(ent_idx + 1, min(len(person_phone_EntityList), ent_idx + 8)):
                after_entity = person_phone_EntityList[after_index]
                if after_entity.entity_type == "phone":
                    distance = (tokens_num_dict[after_entity.sentence_index] + after_entity.begin_index) - (
                            tokens_num_dict[entity.sentence_index] + entity.end_index)
                    phone_nums += 1
                    if distance>100 or phone_nums>=4:
                        break
                    sentence_distance = after_entity.sentence_index - entity.sentence_index
                    value = (-1 / 2 * (distance ** 2)) / 10000
                    if sentence_distance == 0:
                        if distance < 80:
                            # value = (-1 / 2 * (distance ** 2)) / 10000
                            t_match_list.append(Match(entity, after_entity, value))
                            match_nums += 1
                            if not person_nums:
                                byNotPerson_match_nums += 1
                            else:
                                break
                    else:
                        if distance < 50:
                            # value = (-1 / 2 * (distance ** 2)) / 10000
                            t_match_list.append(Match(entity, after_entity, value))
                            match_nums += 1
                            if not person_nums:
                                byNotPerson_match_nums += 1
                            else:
                                break
                else:
                    person_nums += 1
            # 前向查找属性
            if ent_idx != 0 and (not match_nums or not byNotPerson_match_nums):
                previous_entity = person_phone_EntityList[ent_idx - 1]
                if previous_entity.entity_type == 'phone':
                    # if previous_entity.sentence_index == entity.sentence_index:
                    distance = (tokens_num_dict[entity.sentence_index] + entity.begin_index) - (
                            tokens_num_dict[previous_entity.sentence_index] + previous_entity.end_index)
                    if distance < 40:
                        # 前向 没有 /10000
                        value = (-1 / 2 * (distance ** 2))
                        t_match_list.append(Match(entity, previous_entity, value))
    # km算法分配求解(person-phone)
    t_match_list = [mat for mat in t_match_list if mat.main_role not in linked_connetPerson and mat.attribute not in linked_phone]
    personphone_result = dispatch(t_match_list)
    personphone_result = sorted(personphone_result, key=lambda x: (x[0].sentence_index, x[0].begin_index))
    for match in personphone_result:
        _person = match[0]
        _phone = match[1]
        if not _person.person_phone:
            _person.person_phone = []
        _person.person_phone.append(_phone)
    # 多个招标人/代理人或者别称
    for idx in range(1,len(pre_entity)):
        _pre_entity = pre_entity[idx]
        if _pre_entity in linked_company and _pre_entity.label==5:
            last_ent = pre_entity[idx-1]
            if last_ent.entity_type in ['company','org'] and last_ent.label in [0,1]:
                if last_ent.sentence_index==_pre_entity.sentence_index:
                    mid_text = list_sentence[_pre_entity.sentence_index].sentence_text[last_ent.wordOffset_end:_pre_entity.wordOffset_begin]
                    if len(mid_text)<=20 and "，" not in mid_text and re.search("[、\(（]",mid_text):
                        _pre_entity.label = last_ent.label
                        _pre_entity.values[last_ent.label] = 0.6
    # 2022/01/25 固定电话可连多个联系人
    temp_person_entitys = [entity for entity in pre_entity if entity.entity_type == 'person']
    temp_person_entitys2 = [] #和固定电话相连的联系人
    for entity in temp_person_entitys:
        if entity.person_phone:
            for _phone in entity.person_phone:
                if not re.search("^1[3-9]\d{9}$", _phone.entity_text):
                    temp_person_entitys2.append(entity)
                    break
    for index in range(len(temp_person_entitys)):
        entity = temp_person_entitys[index]
        if entity in temp_person_entitys2:
            last_person = entity
            for after_index in range(index + 1, min(len(temp_person_entitys), index + 5)):
                after_entity = temp_person_entitys[after_index]
                if after_entity.sentence_index == last_person.sentence_index and after_entity.begin_index - last_person.end_index < 3:
                    for _phone in entity.person_phone:
                        if not re.search("^1[3-9]\d{9}$", _phone.entity_text):
                            if _phone not in after_entity.person_phone:
                                after_entity.person_phone.append(_phone)
                    last_person = after_entity
                else:
                    break
            if index==0:
                continue
            last_person = entity
            for before_index in range(index-1, max(-1,index-5), -1):
                before_entity = temp_person_entitys[before_index]
                if before_entity.sentence_index == last_person.sentence_index and last_person.begin_index - before_entity.end_index < 3:
                    for _phone in entity.person_phone:
                        if not re.search("^1[3-9]\d{9}$", _phone.entity_text):
                            if _phone not in before_entity.person_phone:
                                before_entity.person_phone.append(_phone)
                    last_person = before_entity
                else:
                    break
    # 更新person为招标/代理联系人的联系方式
    for k in PackDict.keys():
        for i in range(len(PackDict[k]["roleList"])):
            if PackDict[k]["roleList"][i].role_name == "tenderee":
                for _person in person_list:
                    if _person.label==1:#招标联系人
                        person_phone = [phone for phone in _person.person_phone] if _person.person_phone else []
                        for _p in person_phone:
                            PackDict[k]["roleList"][i].linklist.append((_person.entity_text, _p.entity_text))
                        if not person_phone:
                            PackDict[k]["roleList"][i].linklist.append((_person.entity_text,""))
            if PackDict[k]["roleList"][i].role_name == "agency":
                for _person in person_list:
                    if _person.label==2:#代理联系人
                        person_phone = [phone for phone in _person.person_phone] if _person.person_phone else []
                        for _p in person_phone:
                            PackDict[k]["roleList"][i].linklist.append((_person.entity_text, _p.entity_text))
                        if not person_phone:
                            PackDict[k]["roleList"][i].linklist.append((_person.entity_text,""))
    # 更新 PackDict
    not_sure_linked = []
    for link_p in list(linked_company):
        for k in PackDict.keys():
            for i in range(len(PackDict[k]["roleList"])):
                if PackDict[k]["roleList"][i].role_name == "tenderee":
                    if PackDict[k]["roleList"][i].entity_text != link_p.entity_text and link_p.label == 0:
                        not_sure_linked.append(link_p)
                        continue
                    if PackDict[k]["roleList"][i].entity_text == link_p.entity_text:
                        for per in link_p.pointer_person:
                            person_phone = [phone for phone in per.person_phone] if per.person_phone else []
                            if not person_phone:
                                if per.entity_text not in agency_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, ""))
                                    continue
                            for _p in person_phone:
                                if per.entity_text not in agency_contact and _p.entity_text not in agency_phone:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, _p.entity_text))
                elif PackDict[k]["roleList"][i].role_name == "agency":
                    if PackDict[k]["roleList"][i].entity_text != link_p.entity_text and link_p.label == 1:
                        not_sure_linked.append(link_p)
                        continue
                    if PackDict[k]["roleList"][i].entity_text == link_p.entity_text:
                        for per in link_p.pointer_person:
                            person_phone = [phone for phone in per.person_phone] if per.person_phone else []
                            if not person_phone:
                                if per.entity_text not in tenderee_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, ""))
                                    continue
                            for _p in person_phone:
                                if per.entity_text not in tenderee_contact and _p.entity_text not in tenderee_phone:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, _p.entity_text))
                else:
                    if PackDict[k]["roleList"][i].entity_text == link_p.entity_text:
                        for per in link_p.pointer_person:
                            person_phone = [phone for phone in per.person_phone] if per.person_phone else []
                            if not person_phone:
                                if per.entity_text not in tenderee_contact and per.entity_text not in agency_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, ""))
                                    winter_contact.add(per.entity_text)
                                    continue
                            for _p in person_phone:
                                if per.entity_text not in tenderee_contact and _p.entity_text not in tenderee_phone and \
                                        per.entity_text not in agency_contact and _p.entity_text not in agency_phone:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, _p.entity_text))
                                    winter_contact.add(per.entity_text)
    # 更新org/company实体label为0，1的链接
    for link_p in not_sure_linked:
        for k in PackDict.keys():
            for i in range(len(PackDict[k]["roleList"])):
                if PackDict[k]["roleList"][i].role_name == "tenderee":
                    if link_p.label == 0:
                        for per in link_p.pointer_person:
                            person_phone = [phone for phone in per.person_phone] if per.person_phone else []
                            if not person_phone:
                                if per.entity_text not in agency_contact and per.entity_text not in winter_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, ""))
                                    continue
                            for _p in person_phone:
                                if per.entity_text not in agency_contact and _p.entity_text not in agency_phone and per.entity_text not in winter_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, _p.entity_text))
                elif PackDict[k]["roleList"][i].role_name == "agency":
                    if link_p.label == 1:
                        for per in link_p.pointer_person:
                            person_phone = [phone for phone in per.person_phone] if per.person_phone else []
                            if not person_phone:
                                if per.entity_text not in tenderee_contact and per.entity_text not in winter_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, ""))
                                    continue
                            for _p in person_phone:
                                if per.entity_text not in tenderee_contact and _p.entity_text not in tenderee_phone and per.entity_text not in winter_contact:
                                    PackDict[k]["roleList"][i].linklist.append((per.entity_text, _p.entity_text))

    re_split = re.compile("[^\u4e00-\u9fa5、](十一|十二|十三|十四|十五|一|二|三|四|五|六|七|八|九|十)、")
    split_list = [0] * 16
    split_dict = {
        "一、": 1,
        "二、": 2,
        "三、": 3,
        "四、": 4,
        "五、": 5,
        "六、": 6,
        "七、": 7,
        "八、": 8,
        "九、": 9,
        "十、": 10,
        "十一、": 11,
        "十二、": 12,
        "十三、": 13,
        "十四、": 14,
        "十五、": 15
    }

    for item in re.finditer(re_split, _content):
        _index = split_dict.get(item.group()[1:])
        if not split_list[_index]:
            split_list[_index] = item.span()[0] + 1
    split_list = [i for i in split_list if i != 0]
    start = 0
    new_split_list = []
    for idx in split_list:
        new_split_list.append((start, idx))
        start = idx
    new_split_list.append((start, len(_content)))
    # 实体列表按照“公告分段”分组
    words_num_dict = dict()
    last_words_num = 0
    for sentence in list_sentence:
        _index = sentence.sentence_index
        if _index == 0:
            words_num_dict[_index] = 0
        else:
            words_num_dict[_index] = words_num_dict[_index - 1] + last_words_num
        last_words_num = len(sentence.sentence_text)

    # 公司-联系人连接（km算法）
    re_phone = re.compile('1[3-9][0-9][-—－―]?\d{4}[-—－―]?\d{4}|'
                       '\+86.?1[3-9]\d{9}|'
                       '0[1-9]\d{1,2}[-—－―][1-9]\d{6,7}/[1-9]\d{6,10}|'
                       '0[1-9]\d{1,2}[-—－―]\d{7,8}.?转\d{1,4}|'
                       '0[1-9]\d{1,2}[-—－―]\d{7,8}[-—－―]\d{1,4}|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=1[3-9]\d{9})|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?)|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?(?=[1-9]\d{6,7})|'
                       '0[1-9]\d{1,2}[-—－―]?[1-9]\d{6}\d?|'
                       '[\（|\(]0[1-9]\d{1,2}[\）|\)]-?\d{7,8}-?\d{,4}|'
                       '[2-9]\d{6,7}')
    key_phone = re.compile("联系方式|电话|联系人|负责人")
    temporary_list2 = []
    for entity in list_entity:
        # if entity.entity_type in ['org', 'company', 'person'] and entity.is_tail==False:
        if entity.entity_type in ['org', 'company', 'person']:
            temporary_list2.append(entity)
    temporary_list2 = sorted(temporary_list2, key=lambda x: (x.sentence_index, x.begin_index))
    new_temporary_list2 = []
    for _split in new_split_list:
        temp_list = []
        for _entity in temporary_list2:
            if words_num_dict[_entity.sentence_index] + _entity.wordOffset_begin >= _split[0] and words_num_dict[
                _entity.sentence_index] + _entity.wordOffset_end < _split[1]:
                temp_list.append(_entity)
            elif words_num_dict[_entity.sentence_index] + _entity.wordOffset_begin >= _split[1]:
                break
        new_temporary_list2.append(temp_list)
    # print(new_temporary_list2)
    match_list2 = []
    for split_index in range(len(new_temporary_list2)):
        split_entitys = new_temporary_list2[split_index]
        is_skip = False
        for index in range(len(split_entitys)):
            entity = split_entitys[index]
            if is_skip:
                is_skip = False
                continue
            else:
                if entity.entity_type in ['org', 'company']:
                    if entity.label != 5 or entity.entity_text in roleSet:
                        match_nums = 0
                        for after_index in range(index + 1, min(len(split_entitys), index + 4)):
                            after_entity = split_entitys[after_index]
                            if after_entity.entity_type in ['person']:
                                # 实体为中标人/候选人，联系人已确定类别【1，2】
                                if entity.label in [2, 3, 4] and after_entity.label in [1, 2]:
                                    break
                                if after_entity.label in [1, 2, 3]:
                                    distance = (tokens_num_dict[
                                                    after_entity.sentence_index] + after_entity.begin_index) - (
                                                           tokens_num_dict[entity.sentence_index] + entity.end_index)
                                    sentence_distance = after_entity.sentence_index - entity.sentence_index
                                    if sentence_distance == 0:
                                        if distance < 100:
                                            if (entity.label == 0 and after_entity.label == 1) or (
                                                    entity.label == 1 and after_entity.label == 2):
                                                distance = distance / 100
                                            value = (-1 / 2 * (distance ** 2)) / 10000
                                            match_list2.append(Match(entity, after_entity, value))
                                            match_nums += 1
                                    else:
                                        if distance < 60:
                                            if (entity.label == 0 and after_entity.label == 1) or (
                                                    entity.label == 1 and after_entity.label == 2):
                                                distance = distance / 100
                                            value = (-1 / 2 * (distance ** 2)) / 10000
                                            match_list2.append(Match(entity, after_entity, value))
                                            match_nums += 1
                            if after_entity.entity_type in ['org', 'company']:
                                # 解决在‘地址’中识别出org/company的问题
                                # if entity.label in [0,1] and after_index==index+1 and after_entity.label not in [0,1]:
                                if entity.label != 5 and after_index == index + 1 and (
                                        after_entity.label == entity.label or after_entity.label == 5):
                                    distance = (tokens_num_dict[
                                                    after_entity.sentence_index] + after_entity.begin_index) - (
                                                           tokens_num_dict[entity.sentence_index] + entity.end_index)
                                    if distance < 20:
                                        after_entity_left = list_sentence[after_entity.sentence_index].tokens[max(0,
                                                                                                                  after_entity.begin_index - 10):after_entity.begin_index]
                                        after_entity_right = list_sentence[after_entity.sentence_index].tokens[
                                                             after_entity.end_index + 1:after_entity.end_index + 6]
                                        after_entity_left = "".join(after_entity_left)
                                        if len(after_entity_left) > 20:
                                            after_entity_left = after_entity_left[-20:]
                                        after_entity_right = "".join(after_entity_right)[:10]
                                        if re.search("地，?址", after_entity_left):
                                            is_skip = True
                                            continue
                                        if re.search("\(|（", after_entity_left) and re.search("\)|）",
                                                                                              after_entity_right):
                                            is_skip = True
                                            continue
                                if entity.label in [0, 1] and after_entity.label in [0,
                                                                                     1] and entity.label == after_entity.label:
                                    break
                                if entity.label in [0, 1] and after_entity.label in [0, 1] and split_entitys[
                                    index + 1].entity_type == "person":
                                    break
                                if entity.label in [0, 1] and after_entity.label in [2, 3, 4]:
                                    break
                                if entity.label in [2, 3, 4] and after_entity.label in [0, 1]:
                                    break
                        # 搜索没有联系人的电话
                        mid_tokens = []
                        is_same_sentence = False
                        if index == len(split_entitys) - 1:
                            for i in range(entity.sentence_index, len(list_sentence)):
                                mid_tokens += list_sentence[i].tokens
                            mid_tokens = mid_tokens[entity.end_index + 1:]
                            mid_sentence = "".join(mid_tokens)
                            have_phone = re.findall(re_phone, mid_sentence)
                            if have_phone:
                                if re.findall(re_phone, mid_sentence.split("。")[0]):
                                    is_same_sentence = True
                                _phone = have_phone[0]
                                phone_begin = mid_sentence.find(_phone)
                                if words_num_dict[entity.sentence_index] + entity.wordOffset_begin + phone_begin < \
                                        new_split_list[split_index][1]:
                                    mid_sentence = mid_sentence[max(0, phone_begin - 15):phone_begin].replace("，", "")
                                    if re.search(key_phone, mid_sentence):
                                        distance = 1
                                        if is_same_sentence:
                                            if phone_begin <= 200:
                                                value = (-1 / 2 * (distance ** 2)) / 10000
                                                match_list2.append(Match(entity, (entity, _phone), value))
                                                match_nums += 1
                                        else:
                                            if phone_begin <= 60:
                                                value = (-1 / 2 * (distance ** 2)) / 10000
                                                match_list2.append(Match(entity, (entity, _phone), value))
                                                match_nums += 1
                        else:
                            next_entity = split_entitys[index + 1]
                            if next_entity.entity_type in ["org","company"]:
                                _entity_left = list_sentence[next_entity.sentence_index].sentence_text[max(0, next_entity.wordOffset_begin - 20):next_entity.wordOffset_begin]
                                _entity_left2 = re.sub("，（）\(\):：", "", _entity_left)
                                _entity_left2 = _entity_left2[-5:]
                                if re.search("(地，?址|地，?点)[:：][^，。]*$", _entity_left) or re.search("地址|地点", _entity_left2):
                                    if index + 2<= len(split_entitys) - 1:
                                        next_entity = split_entitys[index + 2]
                            if entity.sentence_index == next_entity.sentence_index:
                                mid_tokens += list_sentence[entity.sentence_index].tokens[
                                              entity.end_index + 1:next_entity.begin_index]
                            else:
                                sentence_index = entity.sentence_index
                                while sentence_index <= next_entity.sentence_index:
                                    mid_tokens += list_sentence[sentence_index].tokens
                                    sentence_index += 1
                                mid_tokens = mid_tokens[entity.end_index + 1:-(len(
                                    list_sentence[next_entity.sentence_index].tokens) - next_entity.begin_index) + 1]
                            mid_sentence = "".join(mid_tokens)
                            have_phone = re.findall(re_phone, mid_sentence)
                            if have_phone:
                                if re.findall(re_phone, mid_sentence.split("。")[0]):
                                    is_same_sentence = True
                                _phone = have_phone[0]
                                phone_begin = mid_sentence.find(_phone)
                                mid_sentence = mid_sentence[max(0, phone_begin - 15):phone_begin].replace("，", "")
                                if re.search(key_phone, mid_sentence):
                                    p_phone = [p.entity_text for p in next_entity.person_phone] if next_entity.person_phone else []
                                    if next_entity.entity_type == 'person' and _phone in p_phone:
                                        pass
                                    else:
                                        distance = (tokens_num_dict[
                                                        next_entity.sentence_index] + next_entity.begin_index) - (
                                                           tokens_num_dict[entity.sentence_index] + entity.end_index)
                                        distance = distance / 2
                                        if is_same_sentence:
                                            if phone_begin <= 200:
                                                value = (-1 / 2 * (distance ** 2)) / 10000
                                                match_list2.append(Match(entity, (entity, _phone), value))
                                                match_nums += 1
                                        else:
                                            if phone_begin <= 60:
                                                value = (-1 / 2 * (distance ** 2)) / 10000
                                                match_list2.append(Match(entity, (entity, _phone), value))
                                                match_nums += 1
                        # 实体无匹配时，尝试前向查找匹配
                        if not match_nums:
                            if (entity.label != 5 or entity.entity_text in roleSet) and entity.values[entity.label] >= 0.5 and index != 0:
                                previous_entity = split_entitys[index - 1]
                                if previous_entity.entity_type == 'person' and previous_entity.label in [1, 2, 3]:
                                    if entity.label in [2, 3, 4] and previous_entity.label in [1, 2]:
                                        continue
                                    if previous_entity.sentence_index == entity.sentence_index:
                                        distance = (tokens_num_dict[entity.sentence_index] + entity.begin_index) - (
                                                tokens_num_dict[
                                                    previous_entity.sentence_index] + previous_entity.end_index)
                                        if distance < 20:
                                            # 距离相等时，前向添加处罚值
                                            # distance += 1
                                            # 前向 没有 /10000
                                            value = (-1 / 2 * (distance ** 2))
                                            match_list2.append(Match(entity, previous_entity, value))
    # print(match_list2)
    match_list2 = [mat for mat in match_list2 if mat.main_role not in linked_company and mat.attribute not in linked_person]
    # print(match_list2)
    # km算法分配求解
    result2 = dispatch(match_list2)
    # print(result2)
    for match in result2:
        entity = match[0]
        # print(entity.entity_text)
        # print(match.attribute)
        entity_index = list_entity.index(entity)
        is_update = False
        if isinstance(match[1], tuple):
            person_ = ''
            phone_ = match[1][1].split("/") # 分割多个号码
            # print(person_,phone_)
        else:
            person_ = match[1].entity_text
            phone_ = [i.entity_text for i in match[1].person_phone] if match[1].person_phone else []
        for k in PackDict.keys():
            for i in range(len(PackDict[k]["roleList"])):
                if PackDict[k]["roleList"][i].role_name == "tenderee":
                    # if not PackDict[k]["roleList"][i].linklist:
                        if PackDict[k]["roleList"][i].entity_text == entity.entity_text or entity.label == 0:
                            if person_ not in agency_contact and len(set(phone_)&set(agency_phone))==0 and person_ not in winter_contact:
                                if not phone_:
                                    PackDict[k]["roleList"][i].linklist.append((person_, ""))
                                for p in phone_:
                                    # if not person_ and len()
                                    PackDict[k]["roleList"][i].linklist.append((person_, p))
                                is_update = True
                elif PackDict[k]["roleList"][i].role_name == "agency":
                    # if not PackDict[k]["roleList"][i].linklist:
                        if PackDict[k]["roleList"][i].entity_text == entity.entity_text or entity.label == 1 and person_ not in winter_contact:
                            if person_ not in tenderee_contact and len(set(phone_)&set(tenderee_phone))==0:
                                if not phone_:
                                    PackDict[k]["roleList"][i].linklist.append((person_, ""))
                                for p in phone_:
                                    PackDict[k]["roleList"][i].linklist.append((person_, p))
                                is_update = True
                else:
                    if PackDict[k]["roleList"][i].entity_text == entity.entity_text:
                        if not PackDict[k]["roleList"][i].linklist:
                            if person_ not in tenderee_contact and len(set(phone_)&set(tenderee_phone))==0 and \
                                    person_ not in agency_contact and len(set(phone_)&set(agency_phone))==0:
                                if not phone_:
                                    PackDict[k]["roleList"][i].linklist.append((person_, ""))
                                for p in phone_:
                                    PackDict[k]["roleList"][i].linklist.append((person_, p))
                                is_update = True
        if not person_:
            is_update = False
        if is_update:
            # 更新 list_entity
            if not list_entity[entity_index].pointer_person:
                list_entity[entity_index].pointer_person = []
            list_entity[entity_index].pointer_person.append(match[1])

    linked_person = []
    linked_persons_with = []
    for company_entity in [entity for entity in list_entity if entity.entity_type in ['company','org']]:
        if company_entity.pointer_person:
            for _person in company_entity.pointer_person:
                linked_person.append(_person)
                linked_persons_with.append(company_entity)
    # 一个公司对应多个联系人的补充
    person_entitys = [entity for entity in list_entity if entity.entity_type=='person']
    person_entitys = person_entitys[::-1]
    for index in range(len(person_entitys)):
        entity = person_entitys[index]
        prepare_link = []
        if entity not in linked_person:
            prepare_link.append(entity)
            last_person = entity
            for after_index in range(index + 1, min(len(person_entitys), index + 5)):
                after_entity = person_entitys[after_index]
                if after_entity.sentence_index==last_person.sentence_index and last_person.begin_index-after_entity.end_index<5:
                    if after_entity in linked_person:
                        _index = linked_person.index(after_entity)
                        with_company = linked_persons_with[_index]
                        for i in range(len(PackDict["Project"]["roleList"])):
                            if PackDict["Project"]["roleList"][i].role_name == "tenderee":
                                if PackDict["Project"]["roleList"][i].entity_text == with_company.entity_text or with_company.label == 0:
                                    for item in prepare_link:
                                        person_phone = [p.entity_text for p in item.person_phone] if item.person_phone else []
                                        for _p in person_phone:
                                            PackDict["Project"]["roleList"][i].linklist.append((item.entity_text, _p))
                                        with_company.pointer_person.append(item)
                                        linked_person.append(item)
                            elif PackDict["Project"]["roleList"][i].role_name == "agency":
                                if PackDict["Project"]["roleList"][i].entity_text == with_company.entity_text or with_company.label == 1:
                                    for item in prepare_link:
                                        person_phone = [p.entity_text for p in item.person_phone] if item.person_phone else []
                                        for _p in person_phone:
                                            PackDict["Project"]["roleList"][i].linklist.append((item.entity_text, _p))
                                        with_company.pointer_person.append(item)
                                        linked_person.append(item)
                            else:
                                if PackDict["Project"]["roleList"][i].entity_text == with_company.entity_text:
                                    for item in prepare_link:
                                        person_phone = [p.entity_text for p in item.person_phone] if item.person_phone else []
                                        for _p in person_phone:
                                            PackDict["Project"]["roleList"][i].linklist.append((item.entity_text, _p))
                                        with_company.pointer_person.append(item)
                                        linked_person.append(item)
                        break
                    else:
                        prepare_link.append(after_entity)
                        last_person = after_entity
                        continue

    # 统一同类角色的属性
    if PackDict.get("Project"):
        for i in range(len(PackDict["Project"]["roleList"])):
            # if PackDict["Project"]["roleList"][i].role_name in ["tenderee","agency"]:
            for _entity in list_entity:
                if _entity.entity_type in ['org','company']:
                    is_similar = False
                    # entity_text相同
                    if _entity.entity_text==PackDict["Project"]["roleList"][i].entity_text:
                        is_similar = True
                    # entity.label为【0，1】
                    if _entity.label in [0,1] and dict_role_id[str(_entity.label)]==PackDict["Project"]["roleList"][i].role_name:
                        is_similar = True
                    if is_similar:
                        linked_entitys = _entity.linked_entitys
                        if linked_entitys:
                            for linked_entity in linked_entitys:
                                pointer_person = linked_entity.pointer_person if linked_entity.pointer_person else []
                                for _pointer_person in pointer_person:
                                    _phone = [p.entity_text for p in _pointer_person.person_phone] if _pointer_person.person_phone else []
                                    for _p in _phone:
                                        if (_pointer_person.entity_text,_p) not in PackDict["Project"]["roleList"][i].linklist:
                                            PackDict["Project"]["roleList"][i].linklist.append((_pointer_person.entity_text,_p))

    # "roleList"中联系人电话去重
    for i in range(len(PackDict["Project"]["roleList"])):
        # print(123, PackDict["Project"]["roleList"][i].linklist)
        # 带有联系人的电话
        with_person = [person_phone[1] for person_phone in PackDict["Project"]["roleList"][i].linklist if person_phone[0]]
        # 带有电话的联系人
        with_phone = [person_phone[0] for person_phone in PackDict["Project"]["roleList"][i].linklist if person_phone[1]]
        remove_list = []
        for item in PackDict["Project"]["roleList"][i].linklist:
            if not item[0]:
                if item[1] in with_person:
                    # 删除重复的无联系人电话
                    remove_list.append(item)
            elif not item[1]:
                if item[0] in with_phone:
                    remove_list.append(item)
        for _item in remove_list:
            PackDict["Project"]["roleList"][i].linklist.remove(_item)

    # 联系人——电子邮箱链接
    temporary_list3 = [entity for entity in list_entity if entity.entity_type=='email' or (entity.entity_type=='person' and entity.label in [1,2,3])]
    temporary_list3 = sorted(temporary_list3, key=lambda x: (x.sentence_index, x.begin_index))
    new_temporary_list3 = []
    for _split in new_split_list:
        temp_list = []
        for _entity in temporary_list3:
            if words_num_dict[_entity.sentence_index] + _entity.wordOffset_begin >= _split[0] and words_num_dict[
                _entity.sentence_index] + _entity.wordOffset_end < _split[1]:
                temp_list.append(_entity)
            elif words_num_dict[_entity.sentence_index] + _entity.wordOffset_begin >= _split[1]:
                break
        new_temporary_list3.append(temp_list)
    # print(new_temporary_list3)
    match_list3 = []
    for split_index in range(len(new_temporary_list3)):
        split_entitys = new_temporary_list3[split_index]
        for index in range(len(split_entitys)):
            entity = split_entitys[index]
            if entity.entity_type == 'person':
                match_nums = 0
                for after_index in range(index + 1, min(len(split_entitys), index + 4)):
                    after_entity = split_entitys[after_index]
                    if match_nums > 2:
                        break
                    if after_entity.entity_type == 'email':
                        distance = (tokens_num_dict[after_entity.sentence_index] + after_entity.begin_index) - (
                                           tokens_num_dict[entity.sentence_index] + entity.end_index)
                        sentence_distance = after_entity.sentence_index - entity.sentence_index
                        if sentence_distance == 0:
                            if distance < 100:
                                if (entity.label == 0 and after_entity.label == 1) or (
                                        entity.label == 1 and after_entity.label == 2):
                                    distance = distance / 100
                                value = (-1 / 2 * (distance ** 2)) / 10000
                                match_list3.append(Match(entity, after_entity, value))
                                match_nums += 1
                        else:
                            if distance < 60:
                                if (entity.label == 0 and after_entity.label == 1) or (
                                        entity.label == 1 and after_entity.label == 2):
                                    distance = distance / 100
                                value = (-1 / 2 * (distance ** 2)) / 10000
                                match_list3.append(Match(entity, after_entity, value))
                                match_nums += 1
                # 前向查找匹配
                # if not match_nums:
                if index != 0:
                    previous_entity = split_entitys[index - 1]
                    if previous_entity.entity_type == 'email':
                        if previous_entity.sentence_index == entity.sentence_index:
                            distance = (tokens_num_dict[entity.sentence_index] + entity.begin_index) - (
                                    tokens_num_dict[
                                        previous_entity.sentence_index] + previous_entity.end_index)
                            if distance < 30:
                                # 距离相等时，前向添加处罚值
                                # distance += 1
                                # 前向 没有 /10000
                                value = (-1 / 2 * (distance ** 2))
                                match_list3.append(Match(entity, previous_entity, value))
    # print(match_list3)
    # km算法分配求解
    result3 = dispatch(match_list3)
    for match in result3:
        match_person = match[0]
        match_email = match[1]
        match_person.pointer_email = match_email

    # # 1）第一个公司实体的招标人，则看看下一个实体是否为代理人，如果是则联系人错位连接 。2）在同一句中往后找联系人。3）连接不上在整个文章找联系人。
    # temp_ent_list = []  # 临时列表，记录0,1角色及3联系人
    # other_person = []  # 阈值以上的联系人列表
    # link_person = []   # 有电话没联系上角色的person列表
    # other_ent = []
    # link_ent = []
    # found_person = False
    # ent_list = []
    # for entity in list_entity:
    #     if entity.entity_type in ['org','company','person']:
    #         ent_list.append(entity)
    # # ent_list = [entity for entity in list_entity if entity.entity_type in ['org','company','person']]
    # #for list_index in range(len(ent_list)):
    #     #if ent_list[list_index].entity_type in ['org','company'] and ent_list[list_index].label == 0 and list_index+2<len(ent_list) and \
    #        #ent_list[list_index+1].entity_type in ['org','company'] and ent_list[list_index+1].label == 1 and ent_list[list_index+2].entity_type in ['person']:
    #         #ent_list[list_index+1], ent_list[list_index+2] = ent_list[list_index+2], ent_list[list_index+1]
    # # 2020/11/25增加确定角色联系人判断
    # sure_person_set = set([entity.entity_text for entity in ent_list if entity.entity_type == 'person' and entity.label in [1, 2]])
    # # 招标/代理在同一句中交叉情况的处理
    # for index in range(len(ent_list)):
    #     entity = ent_list[index]
    #     if entity.entity_text in roleSet and entity.label in [0, 1] and index+3<len(ent_list):
    #         if entity.sentence_index==ent_list[index+1].sentence_index==ent_list[index+2].sentence_index==ent_list[index+3].sentence_index:
    #             if ent_list[index+1].begin_index - entity.end_index < 30:
    #                 if ent_list[index+1].entity_text in roleSet and ent_list[index+1].label in [0, 1] and entity.label!=ent_list[index+1].label:
    #                     if ent_list[index+2].entity_type=="person" and ent_list[index+3].entity_type=="person" and \
    #                             ent_list[index+2].label==3 and ent_list[index+3].label==3:
    #                         ent_list[index + 1], ent_list[index + 2] = ent_list[index + 2], ent_list[index + 1]
    #
    #
    # for index in range(len(ent_list)):
    #     entity = ent_list[index]
    #     if entity.entity_type=="person":
    #         if str(entity.label) == "0":  # 2020/11/25 非联系人直接跳过
    #             continue
    #         if entity.values[entity.label]>on_value_person:
    #             if str(entity.label)=="1":
    #                 for i in range(len(PackDict["Project"]["roleList"])):
    #                     if PackDict["Project"]["roleList"][i].role_name=="tenderee":
    #                         PackDict["Project"]["roleList"][i].linklist.append((entity.entity_text,entity.person_phone))
    #                         link_person.append(entity.entity_text)
    #                         link_ent.append(PackDict["Project"]["roleList"][i].entity_text)
    #                 # add pointer_person
    #                 for _entity in list_entity:
    #                     if dict_role_id.get(str(_entity.label))=="tenderee":
    #                         for i in range(len(PackDict["Project"]["roleList"])):
    #                             if PackDict["Project"]["roleList"][i].entity_text==_entity.entity_text and PackDict["Project"]["roleList"][i].role_name=="tenderee":
    #                                 _entity.pointer_person = entity
    #             elif str(entity.label)=="2":
    #                 for i in range(len(PackDict["Project"]["roleList"])):
    #                     if PackDict["Project"]["roleList"][i].role_name=="agency":
    #                         PackDict["Project"]["roleList"][i].linklist.append((entity.entity_text,entity.person_phone))
    #                         link_person.append(entity.entity_text)
    #                         link_ent.append(PackDict["Project"]["roleList"][i].entity_text)
    #                 # add pointer_person
    #                 for _entity in list_entity:
    #                     if dict_role_id.get(str(_entity.label))=="agency":
    #                         for i in range(len(PackDict["Project"]["roleList"])):
    #                             if PackDict["Project"]["roleList"][i].entity_text==_entity.entity_text and PackDict["Project"]["roleList"][i].role_name=="agency":
    #                                 _entity.pointer_person = entity
    #             elif str(entity.label)=="3":
    #                 if entity.entity_text in sure_person_set:  # 2020/11/25 排除已经确定角色的联系人
    #                     continue
    #                 #not_link_person.append((entity_after.entity_text,entity_after.person_phone))
    #                 other_person.append(entity.entity_text)
    #                 temp_ent_list.append((entity.entity_text,entity.person_phone,entity))
    #
    #     #if entity.entity_text in roleSet:
    #     if entity.entity_text in roleSet:
    #         if entity.label in [0,1]:
    #             other_ent.append(entity.entity_text)
    #             temp_ent_list.append((entity.entity_text, entity.label,entity))
    #         for behind_index in range(index+1, len(ent_list)):
    #             entity_after = ent_list[behind_index]
    #             if entity_after.sentence_index-entity.sentence_index>=1 or entity_after.entity_type in ['org','company']:   # 只在本句中找联系人
    #                 break
    #             if entity_after.values is not None:
    #                 if entity_after.entity_type=="person":
    #                     if str(entity_after.label) == "0": # 2020/11/25角色后面为非联系人 停止继续往后找
    #                         break
    #                     if entity_after.values[entity_after.label]>on_value_person:
    #                         if str(entity_after.label)=="1":
    #                             for i in range(len(PackDict["Project"]["roleList"])):
    #                                 if PackDict["Project"]["roleList"][i].role_name=="tenderee":
    #                                     PackDict["Project"]["roleList"][i].linklist.append((entity_after.entity_text,entity_after.person_phone))
    #                                     link_person.append(entity_after.entity_text)
    #                                     link_ent.append(PackDict["Project"]["roleList"][i].entity_text)
    #                         elif str(entity_after.label)=="2":
    #                             for i in range(len(PackDict["Project"]["roleList"])):
    #                                 if PackDict["Project"]["roleList"][i].role_name=="agency":
    #                                     PackDict["Project"]["roleList"][i].linklist.append((entity_after.entity_text,entity_after.person_phone))
    #                                     link_person.append(entity_after.entity_text)
    #                                     link_ent.append(PackDict["Project"]["roleList"][i].entity_text)
    #                         elif str(entity_after.label)=="3":
    #                             if entity_after.entity_text in sure_person_set: # 2020/11/25 如果姓名已经出现在确定角色联系人中则停止往后找
    #                                 break
    #                             elif entity_after.begin_index - entity.end_index > 30:#2020/10/25 如果角色实体与联系人实体间隔大于阈值停止
    #                                 break
    #                             for pack in PackDict.keys():
    #                                 for i in range(len(PackDict[pack]["roleList"])):
    #                                     if PackDict[pack]["roleList"][i].entity_text==entity.entity_text:
    #                                         #if entity_after.sentence_index-entity.sentence_index>1 and len(roleList[i].linklist)>0:
    #                                             #break
    #                                         PackDict[pack]["roleList"][i].linklist.append((entity_after.entity_text,entity_after.person_phone))
    #                                         link_person.append(entity_after.entity_text)
    #                                         #add pointer_person
    #                                         entity.pointer_person = entity_after
    #
    # not_link_person = [person for person in other_person if person not in link_person]
    # not_link_ent = [ent for ent in other_ent if ent not in link_ent]
    # if len(not_link_person) > 0 and len(not_link_ent) > 0 :
    #     item = temp_ent_list
    #     for i in range(len(item)):
    #         if item[i][0] in not_link_ent and item[i][1] == 0 and i+3 < len(item):
    #             if item[i+1][0] in other_ent and item[i+1][1] == 1 and item[i+2][0] in other_person and item[i+3][0] in other_person:
    #                 item[i+1], item[i+2] = item[i+2], item[i+1]
    #     for i in range(len(item)-1, -1, -1):
    #         if item[i][0] in not_link_ent:
    #             for pack in PackDict.keys():
    #                 for role in PackDict[pack]["roleList"]:
    #                     if role.entity_text == item[i][0] and len(role.linklist) < 1:
    #                         for j in range(i+1, len(item)):
    #                             if item[j][0] in not_link_person:
    #                                 role.linklist.append(item[j][:2])
    #                                 #add pointer_person
    #                                 item[i][2].pointer_person = item[j][2]
    #                                 break
    #                             else:
    #                                 break
    # # 电话没有联系人的处理
    # role_with_no_phone = []
    # for i in range(len(PackDict["Project"]["roleList"])):
    #     if PackDict["Project"]["roleList"][i].role_name in ["tenderee","agency"]:
    #         if len(PackDict["Project"]["roleList"][i].linklist)==0: # 找出没有联系人的招标/代理人
    #             role_with_no_phone.append(PackDict["Project"]["roleList"][i].entity_text)
    #         else:
    #             phone_nums = 0
    #             for link in PackDict["Project"]["roleList"][i].linklist:
    #                 if link[1]:
    #                     phone_nums += 1
    #                     break
    #             if not phone_nums:
    #                 role_with_no_phone.append(PackDict["Project"]["roleList"][i].entity_text)
    # if role_with_no_phone:
    #     phone_with_person = [entity.person_phone for entity in list_entity if entity.entity_type == "person"]
    #     # phone_with_person = [phone for phone in phone_with_person if phone]
    #
    #     dict_index_sentence = {}
    #     for _sentence in list_sentence:
    #         dict_index_sentence[_sentence.sentence_index] = _sentence
    #     new_entity_list = [entity for entity in list_entity if entity.entity_type in ['org','company','person']]
    #     for index in range(len(new_entity_list)):
    #         entity = new_entity_list[index]
    #         if entity.entity_text in role_with_no_phone:
    #             e_sentence = dict_index_sentence[entity.sentence_index]
    #             entity_right = e_sentence.tokens[entity.end_index:entity.end_index+40]
    #             entity_right = "".join(entity_right)
    #             if index+1<len(new_entity_list) and entity_right.find(new_entity_list[index+1].entity_text)>-1:
    #                 entity_right = entity_right[:entity_right.find(new_entity_list[index+1].entity_text)]
    #             have_phone = re.findall(phone,entity_right)
    #             if have_phone:
    #                 _phone = have_phone[0]
    #                 phone_begin = entity_right.find(_phone)
    #                 if _phone not in phone_with_person and re.search(key_phone,entity_right[:phone_begin]):
    #                     # entity.person_phone = _phone
    #                     for i in range(len(PackDict["Project"]["roleList"])):
    #                         if PackDict["Project"]["roleList"][i].entity_text == entity.entity_text:
    #                             PackDict["Project"]["roleList"][i].linklist.append(('', _phone))

    
    #寻找多标段招标金额
    p_entity = len(list_entity)-1

    set_tenderer_money = set()
    list_tenderer_money = []  #2021/7/16 新增列表，倒序保存所有中标金额
    unit_list = [] #2021/8/17 新增，保存金额单位

    #遍历所有实体
    while(p_entity>=0):
        entity = list_entity[p_entity]
        if entity.entity_type=="money":
            # 2021/12/03 添加成本警戒线、保证金
            if entity.notes in ['保证金', '成本警戒线']:
                packagePointer, _flag = getPackage(PackageList, entity.sentence_index, entity.begin_index,
                                                   "money-" + str(entity.label), MAX_DIS=2, DIRECT="L")
                if packagePointer is None:
                    packageName = "Project"
                else:
                    packageName = packagePointer.entity_text

                if packageName == "Project":
                    # if PackDict["Project"]["tendereeMoney"]<float(entity.entity_text):
                    #     PackDict["Project"]["tendereeMoney"] = float(entity.entity_text)
                    if entity.notes=="保证金" and "bond" not in PackDict["Project"]:
                        PackDict["Project"]["bond"] = float(entity.entity_text)
                    elif entity.notes=="成本警戒线" and "cost_warning" not in PackDict["Project"]:
                        PackDict["Project"]["cost_warning"] = float(entity.entity_text)

                else:
                    if entity.notes == "保证金" and "bond" not in PackDict[packageName]:
                        PackDict[packageName]["bond"] = float(entity.entity_text)
                    elif entity.notes == "成本警戒线" and "cost_warning" not in PackDict[packageName]:
                        PackDict[packageName]["cost_warning"] = float(entity.entity_text)

            elif entity.values[entity.label]>=on_value:
                if str(entity.label)=="1":
                    set_tenderer_money.add(float(entity.entity_text))
                    list_tenderer_money.append(float(entity.entity_text))  # 2021/7/16 新增列表，倒序保存所有中标金额
                    unit_list.append(entity.money_unit)
                # if str(entity.label)=="0":
                if str(entity.label)=="0" and entity.notes!='总投资':
                    '''
                    if p_entity>0:
                        p_before = list_entity[p_entity-1]
                        if p_before.entity_type=="money" and p_before.label==entity.label and p_before.entity_text==entity.entity_text and abs(entity.begin_index-p_before.end_index)<=2:
                            p_entity -= 1
                            continue
                    '''
                    packagePointer,_flag = getPackage(PackageList,entity.sentence_index,entity.begin_index,"money-"+str(entity.label),MAX_DIS=2,DIRECT="L")
                    if packagePointer is None:
                        packageName = "Project"
                    else:
                        packageName = packagePointer.entity_text
                        
                    if packageName=="Project":
                        # if PackDict["Project"]["tendereeMoney"]<float(entity.entity_text):
                        #     PackDict["Project"]["tendereeMoney"] = float(entity.entity_text)
                        if entity.values[entity.label]>on_value:
                            PackDict["Project"]["tendereeMoney"] = float(entity.entity_text)
                            PackDict["Project"]["tendereeMoneyUnit"] = entity.money_unit
                    else:
                        PackDict[packageName]["tendereeMoney"] = float(entity.entity_text)
                        PackDict[packageName]["tendereeMoneyUnit"] = entity.money_unit
                        #add pointer_tendereeMoney
                        packagePointer.pointer_tendereeMoney = entity
        p_entity -= 1            
    
        
    #删除一个机构有多个角色的数据
    #删除重复人、概率不回传
    final_roleList = []
    list_pop = []
    set_tenderer_role = set()
    dict_pack_tenderer_money = dict()

    for pack in PackDict.keys():
        #删除无效包
        if PackDict[pack]["code"]=="" and PackDict[pack]["tendereeMoney"]==0 and len(PackDict[pack]["roleList"])==0:
            list_pop.append(pack)
        for i in range(len(PackDict[pack]["roleList"])):
            if PackDict[pack]["roleList"][i].role_name=="win_tenderer":
                if PackDict[pack]["roleList"][i].money==0:
                    set_tenderer_role.add(PackDict[pack]["roleList"][i])
                    dict_pack_tenderer_money[pack] = [PackDict[pack]["roleList"][i],set()]
    #找到包的中投标金额
    for _index in range(len(PackageList)):
        if "hit" in PackageList[_index]:
            for _hit in list(PackageList[_index]["hit"]):
                _money = float(_hit.split("-")[1]) if _hit.split("-")[0]=="money" else None
                if PackageList[_index]["name"] in dict_pack_tenderer_money and _money is not None:
                    dict_pack_tenderer_money[PackageList[_index]["name"]][1].add(_money)
    #只找到一个中标人和中标金额
    if len(set_tenderer_money)==1 and len(set_tenderer_role)==1:
        list(set_tenderer_role)[0].money = list(set_tenderer_money)[0]
        list(set_tenderer_role)[0].money_unit = unit_list[0]
        # print('一个中标人一个金额：', list(set_tenderer_money)[0])
    #找到一个中标人和多个招标金额
    if len(set_tenderer_money)>1 and len(set_tenderer_role)==1:
        _maxMoney = 0
        _sumMoney = 0
        for _m in list(set_tenderer_money):
            _sumMoney += _m
            if _m>_maxMoney:
                _maxMoney = _m
        if _sumMoney/_maxMoney==2:
            list(set_tenderer_role)[0].money = _maxMoney
            # print('一人多金额分项合计 取最大金额：', _maxMoney)
        else:
            # list(set_tenderer_role)[0].money = _maxMoney
            if min(list_tenderer_money)>200000 and list_tenderer_money[-1]/min(list_tenderer_money)>9000:
                list(set_tenderer_role)[0].money = min(list_tenderer_money)
                list(set_tenderer_role)[0].money_unit = unit_list[list_tenderer_money.index(min(list_tenderer_money))]
                # print('一人多金额 且最小的大于20万第一个金额比最小金额大几千倍的最小中标金额：', min(list_tenderer_money))
            else:
                list(set_tenderer_role)[0].money = list_tenderer_money[-1]  # 2021/7/16 修改 不是单价合计方式取第一个中标金额
                list(set_tenderer_role)[0].money_unit = unit_list[-1] # 金额单位
                # print('一人多金额 取第一个中标金额：', list_tenderer_money[-1])
    #每个包都只找到一个金额
    _flag_pack_money = True
    for k,v in dict_pack_tenderer_money.items():
        if len(v[1])!=1:
            _flag_pack_money = False
    if _flag_pack_money and len(PackageSet)==len(dict_pack_tenderer_money.keys()):
        for k,v in dict_pack_tenderer_money.items():
            v[0].money = list(v[1])[0]
            # print('k,v in dict_pack_tenderer_money.items', k, v)
    # 2021/7/16 #增加判断中标金额是否远大于招标金额逻辑
    for pack in PackDict.keys():
        for i in range(len(PackDict[pack]["roleList"])):
            if PackDict[pack]["tendereeMoney"] > 0:
                # print('金额数据类型：',type(PackDict[pack]["roleList"][i].money))
                if float(PackDict[pack]["roleList"][i].money) >10000000 and \
                        float(PackDict[pack]["roleList"][i].money)/float(PackDict[pack]["tendereeMoney"])>=1000:
                    PackDict[pack]["roleList"][i].money = float(PackDict[pack]["roleList"][i].money) / 10000
                    # print('招标金额校正中标金额')
    # 2022/04/01 #增加判断中标金额是否远小于招标金额逻辑，比例相差10000倍左右（中标金额“万”单位丢失或未识别）
    for pack in PackDict.keys():
        for i in range(len(PackDict[pack]["roleList"])):
            if PackDict[pack]["tendereeMoney"] > 0 and float(PackDict[pack]["roleList"][i].money) > 0.:
                if float(PackDict[pack]["roleList"][i].money) < 1000 and \
                        float(PackDict[pack]["tendereeMoney"])/float(PackDict[pack]["roleList"][i].money)>=9995 and \
                        float(PackDict[pack]["tendereeMoney"])/float(PackDict[pack]["roleList"][i].money)<11000:
                    PackDict[pack]["roleList"][i].money = float(PackDict[pack]["roleList"][i].money) * 10000
    # 2021/7/19 #增加判断中标金额是否远大于第二三中标金额
    for pack in PackDict.keys():
        tmp_moneys = []
        for i in range(len(PackDict[pack]["roleList"])):
            if float(PackDict[pack]["roleList"][i].money) >100000:
                tmp_moneys.append(float(PackDict[pack]["roleList"][i].money))
        if len(tmp_moneys)>2 and max(tmp_moneys)/min(tmp_moneys)>1000:
            for i in range(len(PackDict[pack]["roleList"])):
                if float(PackDict[pack]["roleList"][i].money)/min(tmp_moneys)>1000:
                    PackDict[pack]["roleList"][i].money = float(PackDict[pack]["roleList"][i].money) / 10000
                    # print('通过其他中标人投标金额校正中标金额')
    for item in list_pop:
        PackDict.pop(item)
    # 公告中只有"招标人"且无"联系人"链接时
    if len(PackDict)==1:
        k = list(PackDict.keys())[0]
        if len(PackDict[k]["roleList"])==1:
            if PackDict[k]["roleList"][0].role_name == "tenderee":
                if not PackDict[k]["roleList"][0].linklist:
                    get_contacts = False
                    if not get_contacts:
                        # 根据大纲Outline类召回联系人
                        for outline in list_outline:
                            if re.search("联系人|联系方|联系方式|联系电话|电话|负责人|与.{2,4}联系",outline.outline_summary):
                                for t_person in [p for p in temporary_list2 if p.entity_type=='person' and p.label==3]:
                                    if words_num_dict[t_person.sentence_index] + t_person.wordOffset_begin >= words_num_dict[outline.sentence_begin_index] + outline.wordOffset_begin and words_num_dict[
                                        t_person.sentence_index] + t_person.wordOffset_end < words_num_dict[outline.sentence_end_index] + outline.wordOffset_end:
                                        if t_person.person_phone:
                                            _phone = [p.entity_text for p in t_person.person_phone]
                                            for _p in _phone:
                                                PackDict[k]["roleList"][0].linklist.append((t_person.entity_text, _p))
                                            get_contacts = True
                                            break
                                    elif words_num_dict[t_person.sentence_index] + t_person.wordOffset_begin >= \
                                            words_num_dict[outline.sentence_end_index] + outline.wordOffset_end:
                                        break
                                if not get_contacts:
                                    sentence_phone = phone.findall(outline.outline_text)
                                    if sentence_phone:
                                        PackDict[k]["roleList"][0].linklist.append(("", sentence_phone[0]))
                                        get_contacts = True
                                        break
                    if not get_contacts:
                        # 直接取文中倒数第一个联系人
                        for _entity in temporary_list2[::-1]:
                            if _entity.entity_type=='person' and _entity.label==3:
                                if _entity.person_phone:
                                    _phone = [p.entity_text for p in _entity.person_phone]
                                    for _p in _phone:
                                        PackDict[k]["roleList"][0].linklist.append((_entity.entity_text, _p))
                                    get_contacts = True
                                    break
                    if not get_contacts:
                        # 如果文中只有一个“phone”实体，则直接取为联系人电话
                        if len(phone_entitys) == 1:
                            PackDict[k]["roleList"][0].linklist.append(("", phone_entitys[0].entity_text))
                            get_contacts = True
                    if not get_contacts:
                        # 通过大纲Outline类直接取电话
                        if len(new_split_list) > 1:
                            for _start, _end in new_split_list:
                                temp_sentence = _content[_start:_end]
                                sentence_outline = temp_sentence.split("，:：")[0]
                                if re.search("联系人|联系方|联系方式|联系电话|电话|负责人|与.{2,4}联系", sentence_outline):
                                    sentence_phone = phone.findall(temp_sentence)
                                    if sentence_phone:
                                        PackDict[k]["roleList"][0].linklist.append(("", sentence_phone[0]))
                                        get_contacts = True
                                        break
                    if not get_contacts:
                        # 通过正则提取句子段落进行提取电话
                        contacts_person = "(?:联系人|联系方|联系方式|负责人|电话|联系电话)[:：]?"
                        tenderee_pattern = "(?:(?:采购|招标|议价|议标|比选)(?:人|公司|单位|组织|部门)|建设(?:单位|业主)|(?:采购|招标|甲)方|询价单位|项目业主|业主|业主单位)[^。]{0,5}"
                        contact_pattern_list = [tenderee_pattern + contacts_person,
                                                "(?:采购[^。，]{0,2}项目|采购事项|招标)[^。，]{0,4}" + contacts_person,
                                                "(?:项目|采购)[^。，]{0,4}" + contacts_person,
                                                "(?:报名|报价|业务咨询|业务|投标咨询)[^。，]{0,4}" + contacts_person, ]
                        for _pattern in contact_pattern_list:
                            get_tenderee_contacts = False
                            for regular_match in re.finditer(_pattern, _content):
                                match_text = _content[regular_match.end():regular_match.end() + 40]
                                match_text = match_text.split("。")[0]
                                sentence_phone = phone.findall(match_text)
                                if sentence_phone:
                                    PackDict[k]["roleList"][0].linklist.append(("", sentence_phone[0]))
                                    get_tenderee_contacts = True
                                    break
                            if get_tenderee_contacts:
                                break

    for pack in PackDict.keys():
        for i in range(len(PackDict[pack]["roleList"])):
            PackDict[pack]["roleList"][i] = PackDict[pack]["roleList"][i].getString()
    return PackDict

def initPackageAttr(RoleList,PackageSet):
    '''
    @summary: 根据拿到的roleList和packageSet初始化接口返回的数据
    '''   
    packDict = dict()
    packDict["Project"] = {"code":"","tendereeMoney":0,"roleList":[], 'tendereeMoneyUnit':''}
    for item in list(PackageSet):
        packDict[item] = {"code":"","tendereeMoney":0,"roleList":[], 'tendereeMoneyUnit':''}
    for item in RoleList:
        if packDict[item.packageName]["code"] =="":
            packDict[item.packageName]["code"] = item.packageCode
        # packDict[item.packageName]["roleList"].append(Role(item.role_name,item.entity_text,0,0,0.0,[]))
        packDict[item.packageName]["roleList"].append(Role(item.role_name,item.entity_text,0,0,0.0,[])) #Role(角色名称，实体名称，角色阈值，金额，金额阈值，连接列表，金额单位)
    return packDict
                
def getPackageRoleMoney(list_sentence,list_entity,list_outline):
    '''
    @param:
        list_sentence:文章的句子list
        list_entity:文章的实体list
    @return: 拿到文章的包-标段号-角色-实体名称-金额-联系人-联系电话  
    '''
    # print("=1")
    theRole = getRoleList(list_sentence,list_entity)
    if not theRole:
        return []
    RoleList,RoleSet,PackageList,PackageSet = theRole
    '''
    for item in PackageList:
        # print(item)
    '''
    PackDict = initPackageAttr(RoleList, PackageSet)

    PackDict = findAttributeAfterEntity(PackDict, RoleSet, PackageList, PackageSet, list_sentence, list_entity, list_outline)
    return PackDict

def turnBidWay(bidway):
    if bidway in ("邀请招标","采购方式：邀请"):
        return "邀请招标"
    elif bidway in ("询价","询单","询比","采购方式：询价"):
        return "询价"
    elif bidway in ("竞谈","竞争性谈判","公开竞谈"):
        return "竞争性谈判"
    elif bidway in ("竞争性磋商","磋商"):
        return "竞争性磋商"
    elif bidway in ("竞价","竞标","电子竞价","以电子竞价","电子书面竞投"):
        return "竞价"
    elif bidway in ("公开招标","网上电子投标","网上招标","采购方式：公开","招标为其他"):
        return "公开招标"
    elif bidway in ("单一来源"):
        return "单一来源"
    elif bidway in ("比选"):
        return "比选"
    else:
        return "其他"

my_time_format_pattern = re.compile("((?P<year>\d{4}|\d{2})\s*[-\/年\.]\s*(?P<month>\d{1,2})\s*[-\/月\.]\s*(?P<day>\d{1,2}))")
import time
def my_timeFormat(_time):
    current_year = time.strftime("%Y",time.localtime())
    all_match = re.finditer(my_time_format_pattern,_time)
    time_list = []
    for _match in all_match:
        if len(_match.group())>0:
            legal = True
            year = ""
            month = ""
            day = ""
            for k,v in _match.groupdict().items():
                if k=="year":
                    year = v
                if k=="month":
                    month = v
                if k=="day":
                    day = v
            if year!="":
                if len(year)==2:
                    year = "20"+year
                if int(year)>int(current_year):
                    legal = False
            else:
                legal = False
            if month!="":
                if int(month)>12:
                    legal = False
            else:
                legal = False
            if day!="":
                if int(day)>31:
                    legal = False
            else:
                legal = False
            if legal:
                # return "%s-%s-%s"%(year,month.rjust(2,"0"),day.rjust(2,"0"))
                time_list.append("%s-%s-%s"%(year,month.rjust(2,"0"),day.rjust(2,"0")))
    return time_list

def getTimeAttributes(list_entity,list_sentence):
    time_entitys = [i for i in list_entity if i.entity_type=='time']
    time_entitys = sorted(time_entitys,key=lambda x:(x.sentence_index, x.begin_index))
    list_sentence = sorted(list_sentence,key=lambda x:x.sentence_index)
    dict_time = {
        "time_release": [], # 1 发布时间
        "time_bidopen": [], # 2 开标时间
        "time_bidclose": [], # 3 截标时间
        'time_bidstart': [],  # 12 投标（开始）时间、响应文件接收（开始）时间

        'time_publicityStart': [],  # 4 公示开始时间（公示时间、公示期）
        'time_publicityEnd': [],  # 5 公示截止时间
        'time_getFileStart': [],  # 6 文件获取开始时间（文件获取时间）
        'time_getFileEnd': [],  # 7 文件获取截止时间
        'time_registrationStart': [],  # 8 报名开始时间（报名时间）
        'time_registrationEnd': [],  # 9 报名截止时间
        'time_earnestMoneyStart': [], #10 保证金递交开始时间（保证金递交时间）
        'time_earnestMoneyEnd': [] , # 11 保证金递交截止时间
        'time_commencement':[] , #13 开工日期
        'time_completion': []  # 14 竣工日期
    }
    last_sentence_index = 0
    last_time_type = ""
    last_time_index = {
        'time_bidstart':"time_bidclose",
        'time_publicityStart':"time_publicityEnd",
        'time_getFileStart':"time_getFileEnd",
        'time_registrationStart':"time_registrationEnd",
        'time_earnestMoneyStart':"time_earnestMoneyEnd",
        'time_commencement':"time_completion",
    }
    for entity in time_entitys:
        sentence_text = list_sentence[entity.sentence_index].sentence_text
        entity_left = sentence_text[max(0, entity.wordOffset_begin - 2):entity.wordOffset_begin]
        entity_right = sentence_text[entity.wordOffset_end:entity.wordOffset_end + 3]
        label_prob = entity.values[entity.label]
        entity_text = entity.entity_text
        extract_time = my_timeFormat(entity_text)
        if extract_time:
            if re.search("至|到", entity_left):
                if entity.sentence_index == last_sentence_index:
                    time_type = last_time_index.get(last_time_type)
                    if time_type:
                        dict_time[time_type].append((extract_time[0], 0.5 + label_prob / 10))
                        last_time_type = ""
                        continue
            if entity.label!=0:
                if entity.label==1 and label_prob>0.5:
                    dict_time['time_release'].append((extract_time[0],label_prob))
                    last_time_type = 'time_release'
                elif entity.label==2 and label_prob>0.5:
                    dict_time['time_bidopen'].append((extract_time[0],label_prob))
                    last_time_type = 'time_bidopen'
                elif entity.label==3 and label_prob>0.5:
                    dict_time['time_bidclose'].append((extract_time[0],label_prob))
                    last_time_type = 'time_bidclose'
                elif entity.label==12 and label_prob>0.5:
                    if len(extract_time)==1:
                        if re.search("前|止|截止",entity_right) or re.search("至|止|到",entity_left) or re.search("前",entity_text[-2:]):
                            dict_time['time_bidclose'].append((extract_time[0], label_prob))
                            last_time_type = 'time_bidclose'
                        else:
                            dict_time['time_bidstart'].append((extract_time[0], label_prob))
                            last_time_type = 'time_bidstart'
                    else:
                        dict_time['time_bidstart'].append((extract_time[0],label_prob))
                        dict_time['time_bidclose'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==4 and label_prob>0.5:
                    if len(extract_time)==1:
                        if re.search("前|止|截止",entity_right) or re.search("至|止|到",entity_left) or re.search("前",entity_text[-2:]):
                            dict_time['time_publicityEnd'].append((extract_time[0], label_prob))
                            last_time_type = 'time_publicityEnd'
                        else:
                            dict_time['time_publicityStart'].append((extract_time[0], label_prob))
                            last_time_type = 'time_publicityStart'
                    else:
                        dict_time['time_publicityStart'].append((extract_time[0],label_prob))
                        dict_time['time_publicityEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==5 and label_prob>0.5:
                    if len(extract_time)==1:
                        dict_time['time_publicityEnd'].append((extract_time[0], label_prob))
                        last_time_type = 'time_publicityEnd'
                    else:
                        dict_time['time_publicityStart'].append((extract_time[0],label_prob))
                        dict_time['time_publicityEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==6 and label_prob>0.5:
                    if len(extract_time)==1:
                        if re.search("前|止|截止",entity_right) or re.search("至|止|到",entity_left) or re.search("前",entity_text[-2:]):
                            dict_time['time_getFileEnd'].append((extract_time[0], label_prob))
                            last_time_type = 'time_getFileEnd'
                        else:
                            dict_time['time_getFileStart'].append((extract_time[0], label_prob))
                            last_time_type = 'time_getFileStart'
                    else:
                        dict_time['time_getFileStart'].append((extract_time[0],label_prob))
                        dict_time['time_getFileEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==7 and label_prob>0.5:
                    if len(extract_time)==1:
                        dict_time['time_getFileEnd'].append((extract_time[0], label_prob))
                        last_time_type = 'time_getFileEnd'
                    else:
                        dict_time['time_getFileStart'].append((extract_time[0],label_prob))
                        dict_time['time_getFileEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==8 and label_prob>0.5:
                    if len(extract_time)==1:
                        if re.search("前|止|截止",entity_right) or re.search("至|止|到",entity_left) or re.search("前",entity_text[-2:]):
                            dict_time['time_registrationEnd'].append((extract_time[0], label_prob))
                            last_time_type = 'time_registrationEnd'
                        else:
                            dict_time['time_registrationStart'].append((extract_time[0], label_prob))
                            last_time_type = 'time_registrationStart'
                    else:
                        dict_time['time_registrationStart'].append((extract_time[0],label_prob))
                        dict_time['time_registrationEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==9 and label_prob>0.5:
                    if len(extract_time)==1:
                        dict_time['time_registrationEnd'].append((extract_time[0], label_prob))
                        last_time_type = 'time_registrationEnd'
                    else:
                        dict_time['time_registrationStart'].append((extract_time[0],label_prob))
                        dict_time['time_registrationEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==10 and label_prob>0.5:
                    if len(extract_time)==1:
                        if re.search("前|止|截止",entity_right) or re.search("至|止|到",entity_left) or re.search("前",entity_text[-2:]):
                            dict_time['time_earnestMoneyEnd'].append((extract_time[0], label_prob))
                            last_time_type = 'time_earnestMoneyEnd'
                        else:
                            dict_time['time_earnestMoneyStart'].append((extract_time[0], label_prob))
                            last_time_type = 'time_earnestMoneyStart'
                    else:
                        dict_time['time_earnestMoneyStart'].append((extract_time[0],label_prob))
                        dict_time['time_earnestMoneyEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==11 and label_prob>0.5:
                    if len(extract_time)==1:
                        dict_time['time_earnestMoneyEnd'].append((extract_time[0], label_prob))
                        last_time_type = 'time_earnestMoneyEnd'
                    else:
                        dict_time['time_earnestMoneyStart'].append((extract_time[0],label_prob))
                        dict_time['time_earnestMoneyEnd'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==13 and label_prob>0.5:
                    if len(extract_time)==1:
                        if re.search("前|止|截止",entity_right) or re.search("至|止|到",entity_left) or re.search("前",entity_text[-2:]):
                            dict_time['time_completion'].append((extract_time[0], label_prob))
                            last_time_type = 'time_completion'
                        else:
                            dict_time['time_commencement'].append((extract_time[0], label_prob))
                            last_time_type = 'time_commencement'
                    else:
                        dict_time['time_commencement'].append((extract_time[0],label_prob))
                        dict_time['time_completion'].append((extract_time[1],label_prob))
                        last_time_type = ''
                elif entity.label==14 and label_prob>0.5:
                    if len(extract_time)==1:
                        dict_time['time_completion'].append((extract_time[0], label_prob))
                        last_time_type = 'time_completion'
                    else:
                        dict_time['time_commencement'].append((extract_time[0],label_prob))
                        dict_time['time_completion'].append((extract_time[1],label_prob))
                        last_time_type = ''
                else:
                    last_time_type = ""
            else:
                last_time_type = ""
        else:
            last_time_type = ""
        last_sentence_index = entity.sentence_index


    result_dict = dict((key,"") for key in dict_time.keys())
    for time_type,value in dict_time.items():
        list_time = dict_time[time_type]
        if list_time:
            list_time.sort(key=lambda x:x[1],reverse=True)
            result_dict[time_type] = list_time[0][0]
    return result_dict

def getOtherAttributes(list_entity):
    dict_other = {"moneysource":"",
                  "person_review":[],
                  "serviceTime":"",
                  "product":[],
                  "total_tendereeMoney":0,
                  "total_tendereeMoneyUnit":''}

    for entity in list_entity:
        if entity.entity_type == 'bidway':
            dict_other["bidway"] = turnBidWay(entity.entity_text)
        elif entity.entity_type=='moneysource':
            dict_other["moneysource"] = entity.entity_text
        elif entity.entity_type=='serviceTime':
            dict_other["serviceTime"] = entity.entity_text
        elif entity.entity_type=="person" and entity.label ==4:
            dict_other["person_review"].append(entity.entity_text)
        elif entity.entity_type=='product':
            dict_other["product"].append(entity.entity_text)
        elif entity.entity_type=='money' and entity.notes=='总投资' and dict_other["total_tendereeMoney"]<float(entity.entity_text):
                dict_other["total_tendereeMoney"] = float(entity.entity_text)
                dict_other["total_tendereeMoneyUnit"] = entity.money_unit

    dict_other["product"] = list(set(dict_other["product"]))
    return dict_other

def getMoneyRange(RoleList):
    pass

def getPREMs(list_sentences,list_entitys,list_articles,list_outlines):
    '''
    @param:
        list_sentence:所有文章的句子list
        list_entity:所有文章的实体list
    @return:list of dict which include文章的包-角色-实体名称-金额-联系人-联系电话  
    '''
    result = []
    for list_sentence,list_entity,list_article,list_outline in zip(list_sentences,list_entitys,list_articles,list_outlines):
        RoleList = getPackageRoleMoney(list_sentence,list_entity,list_outline)
        result.append(dict({"prem":RoleList,"docid":list_article.doc_id},**getOtherAttributes(list_entity),**getTimeAttributes(list_entity,list_sentence),
                           **{"fingerprint":list_article.fingerprint,"match_enterprise":list_article.match_enterprise,
                              "match_enterprise_type":list_article.match_enterprise_type,"process_time":getCurrent_date(),
                              "attachmentTypes":list_article.attachmentTypes, "bidway": list_article.bidway}))
    return result


if __name__=="__main__":
    '''
    conn = getConnection()
    cursor = conn.cursor()
    #sql = " select distinct A.doc_id from entity_mention A,test_predict_role B where A.entity_id=B.entity_id limit 200"
    sql = " select B.doc_id,B.prem from articles_processed A, articles_validation B where A.id=B.doc_id "
    
    result = []
    
    cursor.execute(sql)
    rows = cursor.fetchall()
    count = 0
    for row in rows:
        
        count += 1
        # print(count)
        doc_id = row[0]
        
        roleList = getPackageRoleMoney(doc_id)
        result.append([doc_id,str(roleList),row[1]])
        ''''''
    with codecs.open("getAttribute.html","w",encoding="utf8") as f:
        f.write('<html><head>\
        <meta http-equiv="Content-Type"\
        content="text/html; charset=UTF-8">\
        </head>\
        <body bgcolor="#FFFFFF">\
        <table border="1">\
        <tr>\
        <td>doc_id</td>\
        <td>角色</td>\
        </tr>')
        for item in result:
            f.write("<tr>"+"<td>"+item[0]+"</td>"+"<td>"+item[1]+"</td>"+"<td>"+item[2]+"</td>"+"</tr>")
        f.write("</table></body>")
    '''