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","."]
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      directory = dl_manager.download_and_extract(
          {
              "train": _TRAINURL,
              "validation": _VALIDATIONURL,
              "test": _TESTURL,
          }
      )
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs={"filepath": directory["train"]},
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs={"filepath": directory["validation"]},
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs={"filepath": directory["test"]},
          ),
      ]
  
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 2 for calling the Gap obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list