          print("ent", ent.text, ent.label_, ent.kb_id_)
  
  
  if __name__ == "__main__":
      _read_wikipedia_prior_probs()
  
      # nlp = spacy.load('en_core_web_sm')
      # my_kb = create_kb(nlp.vocab)
      # add_el(my_kb, nlp)
  
 
</s> remove     # nlp = spacy.load('en_core_web_sm')
    # my_kb = create_kb(nlp.vocab)
 </s> add     # STEP 2 : create KB
    nlp = spacy.load('en_core_web_sm')
    my_kb = create_kb(nlp.vocab, max_entities_per_alias=10, min_occ=5) </s> remove     # TODO remove hardcoded path
    with bz2.open('C:/Users/Sofie/Documents/data/wikipedia/enwiki-20190320-pages-articles-multistream.xml.bz2', mode='rb') as file:
 </s> add     with bz2.open(ENWIKI_DUMP, mode='rb') as file: </s> remove     # _read_wikidata()
    _read_wikipedia()
 </s> add  </s> remove def create_kb(vocab):
 </s> add def create_kb(vocab, max_entities_per_alias, min_occ): </s> remove     # adding entities
    # kb.add_entity(entity=entity, prob=prob)
 </s> add     _add_entities(kb)
    _add_aliases(kb, max_entities_per_alias, min_occ)
    # STEP 1 : create prior probabilities from WP
    # run only once !
    # _read_wikipedia_prior_probs()
          print("ent", ent.text, ent.label_, ent.kb_id_)
  
  
  if __name__ == "__main__":
    # STEP 1 : create prior probabilities from WP
    # run only once !
    # _read_wikipedia_prior_probs()
  
      # nlp = spacy.load('en_core_web_sm')
      # my_kb = create_kb(nlp.vocab)
      # add_el(my_kb, nlp)
  
keep keep keep keep replace keep keep keep keep keep
 poc with few entities and collecting aliases from the WP links 
examples/pipeline/wikidata_entity_linking.py