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
docstr: Dataset data in json format
docstr_tok: ["Dataset","data","in","json","format"]
code: def json(self):
      """Dataset data in json format"""
      intents = {
          intent_data.intent_name: intent_data.json
          for intent_data in self.intents
      }
      entities = {entity.name: entity.json for entity in self.entities}
      return dict(
          language=self.language, intents=intents, entities=entities
      )
  
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 7 for calling the Dataset obj's underlying member method code with example usage: obj.json() and returns: dict