          dev=False,
          limit=train_inst,
          kb=kb,
      )
  
      # for testing, get all pos instances (independently of KB)
      dev_data = wikipedia_processor.read_training(
 
</s> remove     # for testing, get all pos instances, whether or not they are in the kb
    dev_data = training_set_creator.read_training(
 </s> add     # for testing, get all pos instances (independently of KB)
    dev_data = wikipedia_processor.read_training( </s> remove     train_data = training_set_creator.read_training(
 </s> add     train_data = wikipedia_processor.read_training( </s> remove     # STEP 3: create and train the entity linking pipe
    logger.info("STEP 3: training Entity Linking pipe")
 </s> add     # STEP 3: create and train an entity linking pipe
    logger.info("STEP 3: Creating and training an Entity Linking pipe")
        labels_discard=labels_discard
          dev=False,
          limit=train_inst,
          kb=kb,
        labels_discard=labels_discard
      )
  
      # for testing, get all pos instances (independently of KB)
      dev_data = wikipedia_processor.read_training(
keep keep add keep keep keep keep
 KB extensions and better parsing of WikiData (#4375)

* fix overflow error on windows

* more documentation & logging fixes

* md fix

* 3 different limit parameters to play with execution time

* bug fixes directory locations

* small fixes

* exclude dev test articles from prior probabilities stats

* small fixes

* filtering wikidata entities, removing numeric and meta items

* adding aliases from wikidata also to the KB

* fix adding WD aliases

* adding also new aliases to previously added entities

* fixing comma's

* small doc fixes

* adding subclassof filtering

* append alias functionality in KB

* prevent appending the same entity-alias pair

* fix for appending WD aliases

* remove date filter

* remove unnecessary import

* small corrections and reformatting

* remove WD aliases for now (too slow)

* removing numeric entities from training and evaluation

* small fixes

* shortcut during prediction if there is only one candidate

* add counts and fscore logging, remove FP NER from evaluation

* fix entity_linker.predict to take docs instead of single sentences

* remove enumeration sentences from the WP dataset

* entity_linker.update to process full doc instead of single sentence

* spelling corrections and dump locations in readme

* NLP IO fix

* reading KB is unnecessary at the end of the pipeline

* small logging fix

* remove empty files 
bin/wiki_entity_linking/wikidata_train_entity_linker.py