      parse_descriptions = True
      parse_aliases = False
      parse_claims = False
  
      with bz2.open(wikidata_file, mode='rb') as file:
          line = file.readline()
          cnt = 0
          while line and (not limit or cnt < limit):
              if cnt % 500000 == 0:
                  print(datetime.datetime.now(), "processed", cnt, "lines of WikiData dump")
 
</s> remove             if cnt % 500000 == 0:
                print(datetime.datetime.now(), "processed", cnt, "lines of WikiData dump")
 </s> add             if cnt % 1000000 == 0:
                print(
                    datetime.datetime.now(), "processed", cnt, "lines of WikiData JSON dump"
                ) </s> remove         while line:
            if cnt % 5000000 == 0:
                print(now(), "processed", cnt, "lines of Wikipedia dump")
 </s> add         while line and (not limit or cnt < limit):
            if cnt % 25000000 == 0:
                print(now(), "processed", cnt, "lines of Wikipedia XML dump")
    with bz2.open(wikidata_file, mode="rb") as file:
      parse_descriptions = True
      parse_aliases = False
      parse_claims = False
  
    with bz2.open(wikidata_file, mode="rb") as file:
          line = file.readline()
          cnt = 0
          while line and (not limit or cnt < limit):
              if cnt % 500000 == 0:
                  print(datetime.datetime.now(), "processed", cnt, "lines of WikiData dump")
keep keep keep keep replace keep keep keep keep keep
 CLI scripts for entity linking (wikipedia & generic) (#4091)

* document token ent_kb_id

* document span kb_id

* update pipeline documentation

* prior and context weights as bool's instead

* entitylinker api documentation

* drop for both models

* finish entitylinker documentation

* small fixes

* documentation for KB

* candidate documentation

* links to api pages in code

* small fix

* frequency examples as counts for consistency

* consistent documentation about tensors returned by predict

* add entity linking to usage 101

* add entity linking infobox and KB section to 101

* entity-linking in linguistic features

* small typo corrections

* training example and docs for entity_linker

* predefined nlp and kb

* revert back to similarity encodings for simplicity (for now)

* set prior probabilities to 0 when excluded

* code clean up

* bugfix: deleting kb ID from tokens when entities were removed

* refactor train el example to use either model or vocab

* pretrain_kb example for example kb generation

* add to training docs for KB + EL example scripts

* small fixes

* error numbering

* ensure the language of vocab and nlp stay consistent across serialization

* equality with =

* avoid conflict in errors file

* add error 151

* final adjustements to the train scripts - consistency

* update of goldparse documentation

* small corrections

* push commit

* turn kb_creator into CLI script (wip)

* proper parameters for training entity vectors

* wikidata pipeline split up into two executable scripts

* remove context_width

* move wikidata scripts in bin directory, remove old dummy script

* refine KB script with logs and preprocessing options

* small edits

* small improvements to logging of EL CLI script 
bin/wiki_entity_linking/wikidata_processor.py