class_docstr: The AI2 ARC dataset with Information Retrieval.
  
  Compared to the normal AI2 corpus, this adds a paragraph containing retrieved
  facts similar to the question + answers.
  
  Retrieved sentences are obtained following the UnifiedQA paper:
  https://arxiv.org/abs/2005.00700
class_docstr_tok: ["The","AI2","ARC","dataset","with","Information","Retrieval",".","Compared","to","the","normal","AI2","corpus",",","this","adds","a","paragraph","containing","retrieved","facts","similar","to","the","question","+","answers",".","Retrieved","sentences","are","obtained","following","the","UnifiedQA","paper",":","https",":","\/\/arxiv.org\/abs\/2005.00700"]
code: def _info(self):
      # Most questions have four possible answers, but a few have five.
      options = ["A", "B", "C", "D", "E"]
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "id": tfds.features.Text(),
                  "question": tfds.features.Text(),
                  "choices": tfds.features.Sequence(
                      {
                          "text": tfds.features.Text(),
                          "label": tfds.features.ClassLabel(
                              names=options
                          ),
                      }
                  ),
                  "answerKey": tfds.features.ClassLabel(names=options),
                  "paragraph": tfds.features.Text(),
              }
          ),
          supervised_keys=None,
          homepage=_HOMEPAGE,
      )
  
file_path: datasets/tensorflow_datasets/datasets/ai2_arc_with_ir/ai2_arc_with_ir_dataset_builder.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import json
  import os
  from etils import epath
  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