class_docstr: TriviaQA is a reading comprehension dataset containing over 650K question-answer-evidence triples
code: def _info(self):
      features = datasets.Features(
          {
              "question_id": datasets.Value("string"),
              "question_source": datasets.Value("string"),
              "question": datasets.Value("string"),
              "answer": {
                  "aliases": datasets.features.Sequence(
                      datasets.Value("string"),
                  ),
                  "value": datasets.Value("string"),
              },
              "search_results": datasets.features.Sequence(
                  {
                      "description": datasets.Value("string"),
                      "filename": datasets.Value("string"),
                      "rank": datasets.Value("int32"),
                      "title": datasets.Value("string"),
                      "url": datasets.Value("string"),
                      "search_context": datasets.Value("string"),
                  }
              ),
          }
      )
      return datasets.DatasetInfo(
          description=_DESCRIPTION,
          features=features,
          homepage=_HOMEPAGE,
          license=_LICENSE,
          citation=_CITATION,
      )
  
file_path: lm-evaluation-harness/lm_eval/datasets/triviaqa/triviaqa.py
imports: import json
  import os
  import datasets
label_desc: Use image node_id 1 for calling the Triviaqa obj's underlying member method code with example usage: obj._info() and returns: datasets