      incl_prior: bool,
      incl_context: bool,
      get_candidates: Callable[[KnowledgeBase, "Span"], Iterable[Candidate]],
  ):
      """Construct an EntityLinker component.
  
      model (Model[List[Doc], Floats2d]): A model that learns document vector
          representations. Given a batch of Doc objects, it should return a single
 
</s> remove     kb (KnowledgeBase): The knowledge-base to link entities to.
 </s> add  </s> remove     kb_loader: Callable[[Vocab], KnowledgeBase],
 </s> add  </s> remove         kb_loader: Callable[[Vocab], KnowledgeBase],
 </s> add  </s> remove         kb_loader (Callable[[Vocab], KnowledgeBase]): A function that creates a KnowledgeBase from a Vocab instance.
 </s> add 
    entity_vector_length: int,
      incl_prior: bool,
      incl_context: bool,
    entity_vector_length: int,
      get_candidates: Callable[[KnowledgeBase, "Span"], Iterable[Candidate]],
  ):
      """Construct an EntityLinker component.
  
      model (Model[List[Doc], Floats2d]): A model that learns document vector
          representations. Given a batch of Doc objects, it should return a single
keep add keep keep keep keep keep keep
 move kb_loader to initialize for NEL instead of constructor 
spacy/pipeline/entity_linker.py