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gap

  • Description:

GAP is a gender-balanced dataset containing 8,908 coreference-labeled pairs of (ambiguous pronoun, antecedent name), sampled from Wikipedia and released by Google AI Language for the evaluation of coreference resolution in practical applications.

Split Examples
'test' 2,000
'train' 2,000
'validation' 454
  • Features:
FeaturesDict({
    'A': Text(shape=(), dtype=tf.string),
    'A-coref': tf.bool,
    'A-offset': tf.int32,
    'B': Text(shape=(), dtype=tf.string),
    'B-coref': tf.bool,
    'B-offset': tf.int32,
    'ID': Text(shape=(), dtype=tf.string),
    'Pronoun': Text(shape=(), dtype=tf.string),
    'Pronoun-offset': tf.int32,
    'Text': Text(shape=(), dtype=tf.string),
    'URL': Text(shape=(), dtype=tf.string),
})
@article{DBLP:journals/corr/abs-1810-05201,
  author    = {Kellie Webster and
               Marta Recasens and
               Vera Axelrod and
               Jason Baldridge},
  title     = {Mind the {GAP:} {A} Balanced Corpus of Gendered Ambiguous Pronouns},
  journal   = {CoRR},
  volume    = {abs/1810.05201},
  year      = {2018},
  url       = {http://arxiv.org/abs/1810.05201},
  archivePrefix = {arXiv},
  eprint    = {1810.05201},
  timestamp = {Tue, 30 Oct 2018 20:39:56 +0100},
  biburl    = {https://dblp.org/rec/bib/journals/corr/abs-1810-05201},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}