class_docstr: Holds loaded intent and entity training data.
class_docstr_tok: ["Holds","loaded","intent","and","entity","training","data","."]
docstr: Return examples which have come from NLU training data.
  
  E.g. If the example came from a story or domain it is not included.
  
  Returns:
      List of NLU training examples.
docstr_tok: ["Return","examples","which","have","come","from","NLU","training","data",".","E.g",".","If","the","example","came","from","a","story","or","domain","it","is","not","included",".","Returns",":","List","of","NLU","training","examples","."]
code: def nlu_examples(self) -> List[Message]:
      """Return examples which have come from NLU training data.
  
      E.g. If the example came from a story or domain it is not included.
  
      Returns:
          List of NLU training examples.
      """
      return [
          ex
          for ex in self.training_examples
          if not ex.is_core_or_domain_message()
      ]
  
imports: import logging
  import os
  from pathlib import Path
  import random
  from collections import Counter, OrderedDict
  import copy
  from os.path import relpath
  from typing import Any, Dict, List, Optional, Set, Text, Tuple, Callable
  import operator
  import rasa.shared.data
  from rasa.shared.utils.common import lazy_property
  import rasa.shared.utils.io
  from rasa.shared.nlu.constants import RESPONSE, INTENT_RESPONSE_KEY, ENTITY_ATTRIBUTE_TYPE, ENTITY_ATTRIBUTE_GROUP, ENTITY_ATTRIBUTE_ROLE, NO_ENTITY_TAG, INTENT, ENTITIES, TEXT, ACTION_NAME
  from rasa.shared.nlu.training_data.message import Message
  from rasa.shared.nlu.training_data import util
label_desc: Use image node_id 9 for calling the TrainingData obj's underlying member method code with example usage: obj.nlu_examples() and returns: unknown