class_docstr: Intent classifier using simple keyword matching.
  
  The classifier takes a list of keywords and associated intents as an input.
  An input sentence is checked for the keywords and the intent is returned.
class_docstr_tok: ["Intent","classifier","using","simple","keyword","matching",".","The","classifier","takes","a","list","of","keywords","and","associated","intents","as","an","input",".","An","input","sentence","is","checked","for","the","keywords","and","the","intent","is","returned","."]
docstr: Creates a new untrained component (see parent class for full docstring).
docstr_tok: ["Creates","a","new","untrained","component","(","see","parent","class","for","full","docstring",")","."]
code: def create(
      cls,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      execution_context: ExecutionContext,
  ) -> KeywordIntentClassifier:
      """Creates a new untrained component (see parent class for full docstring)."""
      return cls(config, model_storage, resource, execution_context)
  
imports: from __future__ import annotations
  import logging
  import re
  from typing import Any, Dict, Optional, Text, List
  from rasa.engine.graph import GraphComponent, ExecutionContext
  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.constants import DOCS_URL_COMPONENTS
  from rasa.nlu.classifiers.classifier import IntentClassifier
  from rasa.shared.nlu.constants import INTENT, TEXT, INTENT_NAME_KEY, PREDICTED_CONFIDENCE_KEY
  import rasa.shared.utils.io
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.message import Message
label_desc: Use image node_id 3 for calling the KeywordIntentClassifier obj's underlying member method code with example usage: obj.create(cls, config, model_storage, resource, execution_context) and returns: cls