697 lines
25 KiB
Python
697 lines
25 KiB
Python
from elasticsearch7 import Elasticsearch
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from collections import Counter
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from general_functions import save_error, normalize_content
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from funcs import save_to_file_by_address, read_file_by_address, write_to_json
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import datetime
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import os
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# ##################################
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# برای محتوای مواد و احکام قانون که از معاونت قوانین مجلس در ایندکس الاستیک ذخیره شده است
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# qanon_section-v02
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# تحلیل روی بعضی فیلدها می کند و تاریخ های آن را استخراج و تبدیل به فرمت خاص تایم استمپ می کند
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# و در فیدل مناسب در همان ایندکس الاستیک ذخیره میکند
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# توجه : دسترسی به الاستیک باید باشد
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# ##################################
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def es_iterate_all_documents(es, index, pagesize=250, scroll_timeout="25m", **kwargs):
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"""
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Helper to iterate ALL values from a single index
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Yields all the documents.
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"""
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global counter
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global total
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is_first = True
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while True:
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# Scroll next
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if is_first: # Initialize scroll
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# result = es.search(index=index, scroll="2m", **kwargs, body={
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# "size": pagesize
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# })
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result = es.search(
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index=index,
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scroll="2m",
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**kwargs,
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size=pagesize,
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body={
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"query": {
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"bool": {
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"must_not": [
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{"exists": {"field": "nlp_parser.type"}},
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{"match": {"content_len": 0}},
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{"match": {"parse_state": 1}},
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{"match": {"parse_state": 2}}
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]
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}
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}
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}
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)
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total = result["hits"]["total"]["value"]
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print("total = %d" % total)
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is_first = False
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else:
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result = es.scroll(scroll_id=scroll_id, scroll=scroll_timeout)
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scroll_id = result["_scroll_id"]
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hits = result["hits"]["hits"]
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counter += len(hits)
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print("progress -> %.2f %%" % ((counter / total) * 100))
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# Stop after no more docs
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if not hits:
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break
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# Yield each entry
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yield from ({"source": hit["_source"], "id": hit["_id"]} for hit in hits)
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def es_iterate_some_documents(es, index, records, pagesize=250, scroll_timeout="25m", **kwargs):
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global counter
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global total
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is_first = True
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query = {
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"query": {
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"terms": {
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"_id": records
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}
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}
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}
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while True:
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# Scroll next
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if is_first: # Initialize scroll
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# result = es.search(index=index, scroll="2m", **kwargs, body={
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# "size": pagesize
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# })
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result = es.search(
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index=index,
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scroll="2m",
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**kwargs,
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size=pagesize,
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body= query
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)
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total = result["hits"]["total"]["value"]
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print("total = %d" % total)
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is_first = False
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else:
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result = es.scroll(scroll_id=scroll_id, scroll=scroll_timeout)
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scroll_id = result["_scroll_id"]
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hits = result["hits"]["hits"]
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counter += len(hits)
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print("progress -> %.2f %%" % ((counter / total) * 100))
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# Stop after no more docs
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if not hits:
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break
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# Yield each entry
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yield from ({"source": hit["_source"], "id": hit["_id"]} for hit in hits)
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def prepare_data(ner_obj_list):
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ner_data_list = []
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for ner_obj in ner_obj_list:
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ner_data = {
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"key" :ner_obj['ner_key'],
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"value" :ner_obj['ner_value'],
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"begin" :ner_obj['ner_start_token'],
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"end" :ner_obj['ner_end_token'],
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"score" :ner_obj['ner_score']
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}
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ner_data_list.append(ner_data)
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return ner_data_list
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def remove_stop_signs(ner_value):
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ner_temp = ner_value
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for sign in stop_signs:
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ner_temp = ner_temp.lstrip(sign)
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ner_temp = ner_temp.rstrip(sign)
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ner_temp = ner_temp.strip()
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return ner_temp
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def remove_stop_orgs(ner_value):
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if ner_value in stop_orgs:
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return False
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return True
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def relation_finder(all_orgs):
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new_orgs = []
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for index, section in enumerate(all_orgs):
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if index % 1000 == 0:
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print(f"relation finder progress: {(index/len(all_orgs)) * 100:.2f} %")
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# if index > 1000:
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# break
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related_sections = []
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orgs = section['orgs']
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for org in orgs:
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for compare_item in all_orgs:
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compare_item_orgs = compare_item['orgs']
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if section['id'] == compare_item['id']:# جلوگیری از ارتباط یک مقرره با خودش
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continue
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if org in compare_item_orgs:
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# related_sections.append(compare_item['id'])
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related_sections.append({
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'section_id': compare_item['id'],
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'qanon_id': compare_item['qanon_id'],
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'ai_key': org,
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'type': 'ORG',
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'weight': 1,
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})
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#rel_unique_list_sorted_by_repitation = []
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# پیدا کردن سطح ارتباط از طریق شمارش تعداد تکرار ارتباطات
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# rel_counter = Counter(related_sections)
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# rel_unique_list = list(rel_counter.items())
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# rel_unique_list_sorted_by_repitation = sorted(rel_unique_list, key=lambda x: x[1], reverse=True)
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# related_sections = rel_unique_list_sorted_by_repitation
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# related_sections_temp = []
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# for relation in related_sections:
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# related_sections_temp.append({
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# 'related_section_id': relation[0],
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# 'weight': relation[1]
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# })
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new_orgs.append({
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'id': section['id'],
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'qanon_id': section['qanon_id'],
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'orgs': section['orgs'],
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# 'orgs_text': section['orgs_text'],
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'related_sections': related_sections,
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})
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return new_orgs
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def extract_weight(relation_list):
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relation_list_temp = []
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for rel_item in relation_list:
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weight = 0
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rel_labels = []
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current_section_id = rel_item['section_id']
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for item in relation_list:
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if item['section_id'] == current_section_id:
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weight += 1
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rel_labels.append(item['ai_key'])
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for rel_item2 in relation_list_temp:
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if current_section_id == rel_item2['section_id']:
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break
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else:
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relation_list_temp.append({
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"section_id": current_section_id,
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"qanon_id": rel_item['qanon_id'],
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"ai_key": rel_labels,
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"type": rel_item['type'],
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"weight": weight
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})
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return relation_list_temp
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print(datetime.datetime.now())
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index_name_i = "ai_mj_qa_section-v05" # الاستیک موجود روی جی پی یو
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# index_name_o = 'mj_qa_test-v01'
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# is_update_state = False
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index_name_o = "ai_mj_qa_section-v07"
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is_update_state = False
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mapping_o = ""
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es = Elasticsearch(
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"http://127.0.0.1:6900",
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basic_auth=("elastic", "SG*7eGwg+KG2_*-1_mMm")
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)
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try:
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if not es.indices.exists(index=index_name_o):
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response = es.indices.create(index=index_name_o, body=mapping_o)
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# print out the response:
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print("create index response:", response)
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except:
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print("elastic error")
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counter = 0
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total = 0
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id = ""
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try:
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# # رکوردهایی که قبلا با خطا مواجه شده در آدرس زیر قرار دارد
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# address3 = os.getcwd() + '/Flair_NER/data/ner_reg_list_prev2.txt'
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# section_list_text = read_file_by_address(address3)
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# records = section_list_text.splitlines()
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section_list = es_iterate_all_documents(es, index_name_i)
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except Exception as e:
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print(' reading from elastic error! ')
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save_error(0, e)
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stop_signs = [')',']','،','؛','»',')،','-','»،','.','(',')؛','/','\\'
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'.......................................................',
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'..........................................................',
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':..............................................................',
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]
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stop_orgs = ['و','.','0','از','است','هایایرانی','ای','یافته و','یافته',
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'یا دولتی شهرداری','گیری','وزارت.','وزارت خانه های','یافته،',
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'یافته و تروریسم','','خانه','چمن','ذغال','یا شهرداری','یا دولتی']
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stop_orgs2 = ["Acrobasis pyrivorella",
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"Aleurocanthus spiniferus",
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"Amauromyza maculosa",
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"سوسک شاخک بلند آسیایی",
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"Anoplophora glabripennis",
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"Araecerus fasciculatus",
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"Asterolecanium phoenicis",
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"Bactrocera spp",
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"fusca",
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"Cacoecimorpha pronubana",
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"Coccotrypes dactyliperda",
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"Coccus viridis",
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"Cryptophlebia leucotreta",
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"Cydia prunivora",
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"Daphorina citri",
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"مگس گالزای گل داوودی",
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"Epichoristodes acerbella",
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"Epochra canadensis",
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"Euphranta japonica",
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"Eutetranychus",
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"Eutetranychus carpini",
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"عنکبوتی",
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"Eutetranychus hirstii",
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"Gonipterus scutellanus",
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"Leptinotarsa desemlineata",
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"Mackiella phoenicls",
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"Mycetaspis personata",
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"Oligonychus mangiferus",
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"Oligonychus pratensis",
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"Omatissus binotatus",
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"Opogona sacchari",
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"Oryctes spp",
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"Pammene rhediella",
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"Petrobia latens",
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"Phoenicoccus marlani",
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"Phoracantha semipunctata",
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"Planococcus ficus",
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"Platypara poeciloptera",
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"Platyptilia carduidactyla",
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"Popillia japonica",
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"Premnotrypes latithorax",
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"Scaphytopius nitridus",
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"Scirtothrips",
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"سوسک پوستخوار",
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"Scolytus multistriatus",
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"Stenodiplosis sorghicola",
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"Simeotarsenemus",
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"Tetranychus",
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"Toxoptera citricida",
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"Trioza erytreae",
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"Trypodendron domesticum",
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"Tumescoptes truchycorp",
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"Zabrotes subfasciatus",
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"Ascochyta lentis",
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"Fusarium",
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"Cephalosporium maydis",
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"Ceratocystis fimbriata",
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"Cercospora kikuchii",
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"Claviceps purpurea",
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"Cochliobolus heterostrophus",
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"Colletotrichum acutatum",
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"Colletotrichum lagenarium",
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"Cryphonectria parasitica",
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"Cryptodiaporthe populea",
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"Didymella lycopersici",
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"oxysporum",
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"Gaeumannomyces graminis",
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"Glomerella gossypii",
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"Monilinia fructigena",
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"Monilinia fructicola",
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"Phaeoisariopsis griseola",
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"Phaeoramularia angolensis",
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"Phialophora cinerescens",
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"Phialophora gregata",
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"بلایت سیاه سیبزمینی",
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"andina",
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"Phyllosticta solitaria",
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"Phymatotrichopsis omnivora",
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"Plasmodiophora brassicae",
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"pittieriana",
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"Septoria lycopersici",
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"Setosphaeria turcica",
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"جرب پودری سیبزمینی",
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"Spongospora subterranea",
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"Stenocarpella macrospora",
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"Stenocarpella maydis",
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"گال (زگیل ) سیبزمینی",
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"Synchytrium endobioticum",
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"سیبزمینی",
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"Thecaphora solani",
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"سیاهک پاکوتاه گندم",
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"Urocystis cepulae",
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"Uromyces transversalis",
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"potato latent tymovirus",
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"Andean potato mottle comovirus",
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"Banana bract mosaic potyvirus",
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"Banana bunchy top nanavirus",
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"golden mosaic geminivirus",
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"برگ چغندر",
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"Beet leaf curl virus",
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"Cherry rasp leaf nepovirus",
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"Citrus leprosis nucleorhabdovirus",
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"Citrus tatter leaf capillovirus",
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"Citrus variegation ilarvirus",
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"Citrus",
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"Lettuce infectious yellows crinivirus",
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"Little cherry clostrovirus",
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"spindle tuber viroid",
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"dwarf nepovirus",
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"ویروس چروکیدگی توت فرنگی",
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"Tobacco ringspot nepovirus",
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"bushy stunt tombusvirus",
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"ringspot",
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"Burkholderia caryophylli",
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"Citrus greening bacterium",
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"michiganensis",
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"chrysanthemi",
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"Erwinia tracheiphila",
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"syringae",
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"Pseudomonas syringae",
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"Ralstonia solanacearum",
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"Xanthomonas fragariae",
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"Xanthomonas vesicatoria",
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"Xylella fastidiosa",
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"Lime witches",
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"Palm lethal yellowing phytoplasma",
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"Peach rosette phytoplasma",
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"Peach X-disease phytoplasma",
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"Peach yellows phytoplasma",
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"Pear decline phytoplasma",
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"Potato stolbur phytoplasma",
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"Anguina agrostis",
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"Anguina funesta",
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"Anguina graminis",
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"Aphelenchoides fragariae",
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"Globodera rostochiensis",
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"Heterodera trifolii",
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"articlla",
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"Meloidogyne fallax",
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"Pratylenchus coffee",
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"Pratylenchus fallax",
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"citrophilus",
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"Tylenchulus semipenetrans",
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"Aphis gossypii",
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"Bactrocera oleae",
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"Brevipalpus phoenicis",
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"spp",
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"Ceratitis capitata",
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"Epilachna chrysomelina",
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"Lasioderma serricorne",
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"Liriomyza trifolii",
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"Pectinophora gossypiella",
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"بید چغندر قند",
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"Phthorimaea ocellatella",
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"Phyllocoptruta oleivora",
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"Planococcus citri",
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"Polyphagotarsonemus latus",
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"Pseudococcus longispinus",
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"Toxoptera aurantii",
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"Trogoderma spp",
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"Viteus vitifoliae",
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"united states of america",
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"stone fruit",
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"states of america",
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"rosette",
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"petiolaris",
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"pensilvanicum",
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"peanut clump furovirus",
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"orientalis Waterhouse",
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"of america",
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"mop-top furovirus",
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"macrospora",
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"leucoloma Boheman",
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"leucoloma",
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"leaf roll nepovirus",
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"greening",
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"dwarf",
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"bacterium",
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"Thrips palmi Karny",
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"Thecaphora solani Barrus",
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"The Hague",
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"Sugarcane grassy shoot",
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"Striga lutea Lour",
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"Striga hermonthica Benth",
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"Striga euphrasioides",
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"Sternochetus mangiferae",
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"Spodoptera litura Fabricius",
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"Spodoptera frugiperda",
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"Spodoptera eridania Cramer",
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"Solanum elaeagnifolium Cav",
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"Solanum",
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"Sesbania macrocarpa",
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"Satsuma dwarf nepovirus",
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"Salvia lancifolia",
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"Raspberry ringspot nepovirus",
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"Raspberry leaf curl luteovirus",
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"Prostephanus truncatus Horn",
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"Potato yellow dwarf rhabdovirus",
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"Potato black ringspot",
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"Popillia",
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"Polygonum pensilvanicum",
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"Plum pox potyvirus",
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"Pissodes castaneus Degeer",
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"Phytophthora megasperma",
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"Phytophthora cinnamomi Rands",
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"Phymatotrichopsis omnivora Hennebert",
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"Phylloxera vastatrix Planch",
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"Peronosclerospora sorghi",
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"Peronosclerospora philippinensis",
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"Peronosclerospora maydis C",
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"Perkinsiella saccharicida Kirkaldy",
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"Pentalonia nigronervosa Coquerel",
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"Pectinophora scutigera Holdaway",
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"Peanut stripe potyvirus",
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"Pea early browning tobravirus",
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"Parasaissetia nigra Nietner",
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"Parabemisia myricae Kuwana",
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"Palm",
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"Otiorhynchus sulcatus Fabricius",
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"New York",
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"Mycosphaerella dearnessii Barr",
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"Meloidogyne fallax Karssen",
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"Massee",
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"Los Angeles",
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"Lime withes broom",
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"Jacquemontia tamnifolia Griseb",
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"Iridomyrmex",
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"Ipomoea hederacea",
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"High",
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"Helianthus petiolaris",
|
||
"Helianthus lenticularis",
|
||
"Helianthus ciliaris",
|
||
"Haplothrips chinensis",
|
||
"Gymnosporangium globosum",
|
||
"Glomerella gossypii Edgerton",
|
||
"Globodera tabacum",
|
||
"Globodera pallida Behrens",
|
||
"Gilpinia hercyniae Hartig",
|
||
"Flower",
|
||
"Euphorbia marginata Pursh",
|
||
"Euphorbia",
|
||
"Epitrix tuberis Gentner",
|
||
"Emex australis",
|
||
"Dysmicoccus brevipes",
|
||
"Diatraea saccharalis",
|
||
"Cuscuta europaea",
|
||
"Cuscuta epithymum Murr",
|
||
"Cuscuta epilinum Weiche",
|
||
"Cryphonectria parasitica Barr",
|
||
"Cotton leaf curl geminivirus",
|
||
"Corporation",
|
||
"Coccus viridis Green",
|
||
"Citrus leaf rugose ilarvirus",
|
||
"Ceratocystis fagacearum",
|
||
"Ceratitis capitata Wiedemann",
|
||
"Carposina niponensis",
|
||
"Bursaphelenchus mucronatus",
|
||
"Broad bean mottle bromovirus",
|
||
"Bactrocera tryoni Froggatt",
|
||
"Bactrocera oleae Gmelin",
|
||
"Bactrocera dorsalis Hendel",
|
||
"Bactrocera cucurbitae Coquillett",
|
||
"Aspidiella",
|
||
"Apple stem pitting virus",
|
||
"Apple chlorotic leafspot trichovirus",
|
||
"Anoplophora glabripennis)Motschulsky",
|
||
"Anastrepha obliqua Macquart",
|
||
"Amaranthus blitoides S.Wats",
|
||
]
|
||
|
||
novalid = -15000000000
|
||
all_orgs = []
|
||
all_orgs_text = ''
|
||
orgs_list = []
|
||
for index, mentry in enumerate(section_list):
|
||
try:
|
||
# if index > 20000:
|
||
# break
|
||
id = mentry["id"]
|
||
# if not id in records:
|
||
# print(id + ' exists')
|
||
# continue
|
||
entry = mentry["source"]
|
||
content = entry.get("content", "")
|
||
content_ai = entry["content_ai"]
|
||
content_len = entry.get("content_len", "")
|
||
qanon_id = entry.get("qanon_id", "")
|
||
ners = entry['ners_v1']
|
||
current_orgs = []
|
||
|
||
for ner_item in ners:
|
||
if ner_item['key'] == 'ORG':
|
||
ner_temp = remove_stop_signs(ner_item['value'].strip())
|
||
if ner_temp in stop_orgs:
|
||
continue
|
||
if ner_temp in stop_orgs2:
|
||
continue
|
||
if ner_temp.startswith('ها') or ner_temp.startswith('های'):
|
||
continue
|
||
if ('سازمان های' in ner_temp
|
||
or 'سازمان ها' in ner_temp
|
||
or 'وزارت خانها' in ner_temp
|
||
or 'وزارت خانهها' in ner_temp
|
||
or 'وزارت خانههای' in ner_temp
|
||
or 'وزارت خانه' in ner_temp
|
||
or 'وزارت خانه های' in ner_temp
|
||
or 'وزارتین ' in ner_temp
|
||
):
|
||
continue
|
||
if not ('وزارت' in ner_temp or 'سازمان' in ner_temp):
|
||
continue
|
||
ner_temp = normalize_content(ner_temp)
|
||
current_orgs.append(ner_temp)
|
||
|
||
if current_orgs:
|
||
unique_orgs_list = []
|
||
# حذف مقادیر تکراری
|
||
[unique_orgs_list.append(x) for x in current_orgs if x not in unique_orgs_list]
|
||
current_orgs = unique_orgs_list
|
||
# current_org_list_text = ''
|
||
# for c_org in current_orgs:
|
||
# current_org_list_text += c_org + '\n'
|
||
all_orgs.append({
|
||
"id": id,
|
||
"qanon_id": qanon_id,
|
||
"orgs": current_orgs,
|
||
# "orgs_text": current_org_list_text,
|
||
})
|
||
#separator = "*"*100 + '\n'
|
||
#all_orgs_text += f"id: {id}\norgs: {current_orgs}\n\norgs_text: \n{current_org_list_text}\n\ncontentai: {content_ai}\n{separator}"
|
||
# for org in current_orgs:
|
||
# orgs_list.append(org)
|
||
|
||
# all_orgs_relations = relation_finder(all_orgs)
|
||
# print(len(all_orgs_relations))
|
||
# # for i, section in enumerate(all_orgs_relations):
|
||
# # print('rel_task: ' + str(i))
|
||
# data = {
|
||
# "qanon_id" : qanon_id,
|
||
# "content_ai":content_ai,
|
||
# "ners_v1": ners,
|
||
# "relations": all_orgs_relations
|
||
# }
|
||
|
||
# eid = id
|
||
|
||
# try:
|
||
# if is_update_state:
|
||
# resp = es.update(index=index_name_o, id=eid, doc=data)
|
||
# else:
|
||
# #write_to_json(data, './data/regulations_ner.json')
|
||
# resp = es.index(index=index_name_o, id=eid, document=data)
|
||
|
||
|
||
# except Exception as e:
|
||
# save_error(id, e)
|
||
except Exception as error:
|
||
print(error)
|
||
# print('relation task --------------> ' + str(count))
|
||
# if count > 1000 :
|
||
# break
|
||
|
||
# if content_len == 0:
|
||
# continue
|
||
|
||
all_orgs_relations = relation_finder(all_orgs)
|
||
print('all orgs count: ' + str(len(all_orgs_relations)))
|
||
|
||
# section_list_temp = [c for i, c in enumerate(section_list)]
|
||
# شمارش تعداد رکوردها
|
||
# len_section_list_temp = len(section_list_temp)
|
||
count = 0
|
||
section_list1 = es_iterate_all_documents(es, index_name_i)
|
||
for mentry1 in section_list1:
|
||
count += 1
|
||
# if count > 10000:
|
||
# break
|
||
# print('relation task for section: ' + str(count))
|
||
if count % 100 == 0:
|
||
print(f"relation finder progress: {(count / 273442) * 100:.2f} %")
|
||
id1 = mentry1["id"]
|
||
|
||
entry1 = mentry1["source"]
|
||
content1 = entry1.get("content", "")
|
||
content_ai1 = entry1["content_ai"]
|
||
content_len1 = entry1.get("content_len", "")
|
||
qanon_id1 = entry1.get("qanon_id", "")
|
||
ners1 = entry1['ners_v1']
|
||
current_relation_list = []
|
||
# iid = 'mj_qa_section_230085'
|
||
|
||
# if id1 != iid:
|
||
# continue
|
||
# if id1 == iid:
|
||
# x = 10
|
||
current_relations = []
|
||
for i, section in enumerate(all_orgs_relations):
|
||
if section['id'] == id1:
|
||
current_relations = section['related_sections']
|
||
for rel_item in current_relations:
|
||
current_relation_list.append(rel_item)
|
||
current_relation_list = extract_weight(current_relation_list)
|
||
data1 = {
|
||
"qanon_id" : qanon_id1,
|
||
"content_ai": content_ai1,
|
||
"ners_v1": ners1,
|
||
"relations": current_relation_list
|
||
}
|
||
|
||
eid = id1
|
||
|
||
try:
|
||
if is_update_state:
|
||
resp = es.update(index=index_name_o, id=eid, doc=data1)
|
||
else:
|
||
#write_to_json(data, './data/regulations_ner.json')
|
||
resp = es.index(index=index_name_o, id=eid, document=data1)
|
||
#pass
|
||
|
||
|
||
except Exception as e:
|
||
save_error(id, e)
|
||
|
||
print(datetime.datetime.now())
|
||
print(" # # # relation extraction finished! # # # ")
|
||
|
||
|
||
# استفاده از Counter برای شمارش تعداد تکرار هر موجودیت
|
||
'''
|
||
counter = Counter(orgs_list)
|
||
unique_dict = dict(counter)
|
||
unique_list = list(unique_dict.items())
|
||
unique_list_sorted_by_key = sorted(unique_list, key=lambda x: x[1], reverse=True)
|
||
orgs_list = unique_list_sorted_by_key
|
||
org_list_text = ''
|
||
for org in orgs_list:
|
||
org_list_text += str(org[1]) + ' *** '+ org[0] + '\n'
|
||
orgs_address = os.getcwd() + '/Flair_NER/data/all_orgs.txt'
|
||
save_to_file_by_address(orgs_address, org_list_text)
|
||
orgs_text_address = os.getcwd() + '/Flair_NER/data/all_orgs_text.txt'
|
||
save_to_file_by_address(orgs_text_address, all_orgs_text)
|
||
|
||
save_error(id, e)
|
||
'''
|