class_docstr: Entity extractor which uses SpaCy.
class_docstr_tok: ["Entity","extractor","which","uses","SpaCy","."]
docstr: Components that should be included in the pipeline before this component.
docstr_tok: ["Components","that","should","be","included","in","the","pipeline","before","this","component","."]
code: def required_components(cls) -> List[Type]:
      """Components that should be included in the pipeline before this component."""
      return [SpacyNLP]
  
imports: import typing
  from typing import Any, Dict, List, Text, Type
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.shared.nlu.constants import ENTITIES, TEXT
  from rasa.nlu.utils.spacy_utils import SpacyModel, SpacyNLP
  from rasa.nlu.extractors.extractor import EntityExtractorMixin
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 1 for calling the SpacyEntityExtractor obj's underlying member method code with example usage: obj.required_components(cls) and returns: list