class_docstr: Dataset used in the main NLU training API
  
  Consists of intents and entities data. This object can be built either from
  text files (:meth:`.Dataset.from_files`) or from YAML files
  (:meth:`.Dataset.from_yaml_files`).
  
  Attributes:
      language (str): language of the intents
      intents (list of :class:`.Intent`): intents data
      entities (list of :class:`.Entity`): entities data
code: def _ensure_entity_values(self):
      entities_values = {
          entity.name: self._get_entity_values(entity)
          for entity in self.entities
      }
      for intent in self.intents:
          for utterance in intent.utterances:
              for chunk in utterance.slot_chunks:
                  if chunk.text is not None:
                      continue
                  try:
                      chunk.text = next(entities_values[chunk.entity])
                  except StopIteration:
                      raise DatasetFormatError(
                          "At least one entity value must be provided for "
                          "entity '%s'" % chunk.entity
                      )
      return self
  
file_path: snips-nlu/snips_nlu/dataset/dataset.py
imports: from __future__ import print_function, unicode_literals
  import io
  from itertools import cycle
  from snips_nlu.common.utils import unicode_string
  from snips_nlu.dataset.entity import Entity
  from snips_nlu.dataset.intent import Intent
  from snips_nlu.exceptions import DatasetFormatError
label_desc: Use image node_id 5 for calling the Dataset obj's underlying member method code with example usage: obj._ensure_entity_values() and returns: self