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 __init__(self, language, intents, entities):
      self.language = language
      self.intents = intents
      self.entities = entities
      self._add_missing_entities()
      self._ensure_entity_values()
  
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 1 to create a new Dataset object from inherited base classes: object with example: obj = Dataset(language, intents, entities)