class_docstr: Reader for NLU training data.
docstr: Extracts the lookup table from the entity synonyms.
docstr_tok: ["Extracts","the","lookup","table","from","the","entity","synonyms","."]
code: def _extract_lookup_tables(
      entity: Dict[Text, Any], examples: List[Dict[Text, Any]]
  ) -> Optional[List[Dict[Text, Any]]]:
      """Extracts the lookup table from the entity synonyms."""
      synonyms = [e["synonyms"] for e in examples if "synonyms" in e]
      synonyms = DialogflowReader._flatten(synonyms)
      elements = [synonym for synonym in synonyms if "@" not in synonym]
  
      if len(elements) == 0:
          return None
      return [{"name": entity.get("name"), "elements": elements}]
  
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 6 for calling the DialogflowReader obj's underlying member method code with example usage: obj._extract_lookup_tables(entity, examples) and returns: list, None