class_docstr: Extracts entities via lookup tables and regexes defined in the training data.
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 {
          # text will be processed with case insensitive as default
          "case_sensitive": False,
          # use lookup tables to extract entities
          "use_lookup_tables": True,
          # use regexes to extract entities
          "use_regexes": True,
          # use match word boundaries for lookup table
          "use_word_boundaries": True,
      }
  
imports: from __future__ import annotations
  import logging
  import re
  from typing import Any, Dict, List, Optional, Text
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.storage import ModelStorage
  from rasa.engine.storage.resource import Resource
  import rasa.shared.utils.io
  import rasa.nlu.utils.pattern_utils
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.constants import ENTITIES, ENTITY_ATTRIBUTE_VALUE, ENTITY_ATTRIBUTE_START, ENTITY_ATTRIBUTE_END, TEXT, ENTITY_ATTRIBUTE_TYPE
  from rasa.nlu.extractors.extractor import EntityExtractorMixin
label_desc: Use image node_id 1 for calling the RegexEntityExtractor obj's underlying member method code with example usage: obj.get_default_config() and returns: dict