code: def test_process_unfeaturized_input(
      crf_entity_extractor: Callable[
          [Dict[Text, Any]], CRFEntityExtractor
      ],
  ):
      crf_extractor = crf_entity_extractor({})
      message_text = "message text"
      message = Message(data={TEXT: message_text})
      processed_message = crf_extractor.process([message])[0]
  
      assert processed_message.get(TEXT) == message_text
      assert processed_message.get(ENTITIES) == []
  
imports: import copy
  from typing import Dict, Text, List, Any, Callable
  import pytest
  from rasa.engine.graph import ExecutionContext
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.featurizers.dense_featurizer.spacy_featurizer import SpacyFeaturizer
  from rasa.nlu.tokenizers.spacy_tokenizer import SpacyTokenizer
  from rasa.nlu.constants import SPACY_DOCS
  from rasa.nlu.tokenizers.whitespace_tokenizer import WhitespaceTokenizer
  from rasa.nlu.utils.spacy_utils import SpacyModel, SpacyNLP
  from rasa.shared.importers.rasa import RasaFileImporter
  from rasa.shared.nlu.constants import TEXT, ENTITIES
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.extractors.crf_entity_extractor import CRFEntityExtractor, CRFEntityExtractorOptions
label_desc: Use image node_id 5 for calling a global function with example usage: test_process_unfeaturized_input(crf_entity_extractor) without return types