          else:
              return NeuralEntityRecognizer(nlp.vocab, **cfg)
  
      @classmethod
      def create_pipeline(cls, nlp=None):
          meta = nlp.meta if nlp is not None else {}
          # Resolve strings, like "cnn", "lstm", etc
          pipeline = []
          for entry in cls.pipeline:
              factory = cls.Defaults.factories[entry]
 
</s> remove             self.pipeline = self.Defaults.create_pipeline(self)
 </s> add             self.pipeline = self.Defaults.create_pipeline(self, disable) </s> remove             self.pipeline = list(pipeline)
 </s> add             # Careful not to do getattr(p, 'name', None) here
            # If we had disable=[None], we'd disable everything!
            self.pipeline = [p for p in pipeline
                             if p not in disable
                             and getattr(p, 'name', p) not in disable] </s> remove     def __init__(self, vocab=True, make_doc=True, pipeline=None, meta={}, **kwargs):
 </s> add     def __init__(self, vocab=True, make_doc=True, pipeline=None, meta={},
            disable=tuple(), **kwargs):
    def create_pipeline(cls, nlp=None, disable=tuple()):
          else:
              return NeuralEntityRecognizer(nlp.vocab, **cfg)
  
      @classmethod
    def create_pipeline(cls, nlp=None, disable=tuple()):
          meta = nlp.meta if nlp is not None else {}
          # Resolve strings, like "cnn", "lstm", etc
          pipeline = []
          for entry in cls.pipeline:
              factory = cls.Defaults.factories[entry]
keep keep keep keep replace keep keep keep keep keep
 Support disable keyword in Language.__init__ 
spacy/language.py