class_docstr: GAP is a gender-balanced dataset.
  
  It contains 8,908 coreference-labeled pairs
  of (ambiguous pronoun, antecedent name), sampled from Wikipedia.
class_docstr_tok: ["GAP","is","a","gender-balanced","dataset",".","It","contains","8,908","coreference-labeled","pairs","of","(","ambiguous","pronoun",",","antecedent","name",")",",","sampled","from","Wikipedia","."]
code: def _info(self):
      return tfds.core.DatasetInfo(
          builder=self,
          description=_DESCRIPTION,
          features=tfds.features.FeaturesDict(
              {
                  "ID": tfds.features.Text(),
                  "Text": tfds.features.Text(),
                  "Pronoun": tfds.features.Text(),
                  "Pronoun-offset": np.int32,
                  "A": tfds.features.Text(),
                  "A-offset": np.int32,
                  "A-coref": np.bool_,
                  "B": tfds.features.Text(),
                  "B-offset": np.int32,
                  "B-coref": np.bool_,
                  "URL": tfds.features.Text(),
              }
          ),
          supervised_keys=None,
          homepage="https://github.com/google-research-datasets/gap-coreference",
          citation=_CITATION,
      )
  
file_path: datasets/tensorflow_datasets/text/gap.py
imports: from __future__ import annotations
  import csv
  from etils import epath
  import numpy
  from tensorflow_datasets.core.utils import bool_utils
  import tensorflow_datasets.public_api
label_desc: Use image node_id 1 for calling the Gap obj's underlying member method code with example usage: obj._info() and returns: tfds