class_docstr: Entity extractor which uses SpaCy.
class_docstr_tok: ["Entity","extractor","which","uses","SpaCy","."]
docstr: The component's default config (see parent class for full docstring).
docstr_tok: ["The","component","'s","default","config","(","see","parent","class","for","full","docstring",")","."]
code: def get_default_config() -> Dict[Text, Any]:
      """The component's default config (see parent class for full docstring)."""
      return {
          # by default all dimensions recognized by spacy are returned
          # dimensions can be configured to contain an array of strings
          # with the names of the dimensions to filter for
          "dimensions": None
      }
  
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 2 for calling the SpacyEntityExtractor obj's underlying member method code with example usage: obj.get_default_config() and returns: dict