class_docstr: Extracts entities via lookup tables and regexes defined in the training data.
docstr: Creates a new instance.
  
  Args:
      config: The configuration.
      model_storage: Storage which graph components can use to persist and load
          themselves.
      resource: Resource locator for this component which can be used to persist
          and load itself from the `model_storage`.
      patterns: a list of patterns
docstr_tok: ["Creates","a","new","instance",".","Args",":","config",":","The","configuration",".","model_storage",":","Storage","which","graph","components","can","use","to","persist","and","load","themselves",".","resource",":","Resource","locator","for","this","component","which","can","be","used","to","persist","and","load","itself","from","the","`","model_storage","`",".","patterns",":","a","list","of","patterns"]
code: def __init__(
      self,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      patterns: Optional[List[Dict[Text, Text]]] = None,
  ) -> None:
      """Creates a new instance.
  
      Args:
          config: The configuration.
          model_storage: Storage which graph components can use to persist and load
              themselves.
          resource: Resource locator for this component which can be used to persist
              and load itself from the `model_storage`.
          patterns: a list of patterns
      """
      # graph component
      self._config = {**self.get_default_config(), **config}
      self._model_storage = model_storage
      self._resource = resource
      # extractor
      self.case_sensitive = self._config["case_sensitive"]
      self.patterns = patterns or []
  
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 3 to create a new RegexEntityExtractor object from inherited base classes: GraphComponent, EntityExtractorMixin with example: obj = RegexEntityExtractor(config, model_storage, resource, patterns)