class_docstr: TriviaQA is a reading comprehension dataset.
  
  It containss over 650K question-answer-evidence triples.
class_docstr_tok: ["TriviaQA","is","a","reading","comprehension","dataset",".","It","containss","over","650K","question-answer-evidence","triples","."]
code: def _info(self):
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "question": tfds.features.Text(),
                  "question_id": tfds.features.Text(),
                  "question_source": tfds.features.Text(),
                  "entity_pages": tfds.features.Sequence(
                      {
                          "doc_source": tfds.features.Text(),
                          "filename": tfds.features.Text(),
                          "title": tfds.features.Text(),
                          "wiki_context": tfds.features.Text(),
                      }
                  ),
                  "search_results": tfds.features.Sequence(
                      {
                          "description": tfds.features.Text(),
                          "filename": tfds.features.Text(),
                          "rank": np.int32,
                          "title": tfds.features.Text(),
                          "url": tfds.features.Text(),
                          "search_context": tfds.features.Text(),
                      }
                  ),
                  "answer": tfds.features.FeaturesDict(
                      {
                          "aliases": tfds.features.Sequence(
                              tfds.features.Text()
                          ),
                          "normalized_aliases": tfds.features.Sequence(
                              tfds.features.Text()
                          ),
                          "matched_wiki_entity_name": tfds.features.Text(),
                          "normalized_matched_wiki_entity_name": tfds.features.Text(),
                          "normalized_value": tfds.features.Text(),
                          "type": tfds.features.Text(),
                          "value": tfds.features.Text(),
                      }
                  ),
              }
          ),
          supervised_keys=None,
          homepage="http://nlp.cs.washington.edu/triviaqa/",
      )
  
file_path: datasets/tensorflow_datasets/datasets/trivia_qa/trivia_qa_dataset_builder.py
imports: from __future__ import annotations
  import json
  import os
  from absl import logging
  from etils import epath
  import numpy
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Builder obj's underlying member method code with example usage: obj._info() and returns: self