class_docstr: DatasetBuilder for answer_equivalence dataset.
class_docstr_tok: ["DatasetBuilder","for","answer_equivalence","dataset","."]
docstr: Returns the dataset metadata.
docstr_tok: ["Returns","the","dataset","metadata","."]
code: def _info(self) -> tfds.core.DatasetInfo:
      """Returns the dataset metadata."""
      return self.dataset_info_from_configs(
          features=tfds.features.FeaturesDict(
              {
                  "qid": tfds.features.Text(),
                  "gold_index": np.int32,
                  "context": tfds.features.Text(),
                  "question": tfds.features.Text(),
                  "reference": tfds.features.Text(),
                  "candidate": tfds.features.Text(),
                  "score": np.float32,
                  "question_1": tfds.features.ClassLabel(
                      names=["no", "yes", "null"]
                  ),
                  "question_2": tfds.features.ClassLabel(
                      names=["no", "yes", "null"]
                  ),
                  "question_3": tfds.features.ClassLabel(
                      names=["no", "yes", "null"]
                  ),
                  "question_4": tfds.features.ClassLabel(
                      names=["no", "yes", "null"]
                  ),
              }
          ),
          supervised_keys=None,
          homepage="https://github.com/google-research-datasets/answer-equivalence-dataset",
      )
  
file_path: datasets/tensorflow_datasets/datasets/answer_equivalence/answer_equivalence_dataset_builder.py
imports: from __future__ import annotations
  import json
  import os
  from etils import epath
  import numpy
  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