class_docstr: Reader for NLU training data.
docstr: Combines text chunks and extracts entities.
docstr_tok: ["Combines","text","chunks","and","extracts","entities","."]
code: def _join_text_chunks(
      self, chunks: List[Dict[Text, Any]]
  ) -> Tuple[Text, List[Dict[Text, Any]]]:
      """Combines text chunks and extracts entities."""
      utterance = ""
      entities = []
      for chunk in chunks:
          entity = self._extract_entity(chunk, len(utterance))
          if entity:
              entities.append(entity)
          utterance += chunk["text"]
  
      return utterance, entities
  
imports: import logging
  import os
  from pathlib import Path
  from typing import Any, Dict, Optional, Text, List, Tuple, Union
  import rasa.shared.nlu.training_data.util
  from rasa.shared.constants import DOCS_BASE_URL
  from rasa.shared.nlu.training_data.formats.readerwriter import TrainingDataReader
  from rasa.shared.nlu.training_data.util import transform_entity_synonyms
  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 DialogflowReader obj's underlying member method code with example usage: obj._join_text_chunks(chunks) and returns: utterance,  entities