- 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.
Homepage: https://github.com/google-research-datasets/gap-coreference
Source code:
tfds.text.Gap
Versions:
0.1.0
(default): No release notes.
Download size:
2.29 MiB
Dataset size:
Unknown size
Auto-cached (documentation): Unknown
Splits:
Split | Examples |
---|---|
'test' |
2,000 |
'train' |
2,000 |
'validation' |
454 |
- Feature structure:
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),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
A | Text | tf.string | ||
A-coref | Tensor | tf.bool | ||
A-offset | Tensor | tf.int32 | ||
B | Text | tf.string | ||
B-coref | Tensor | tf.bool | ||
B-offset | Tensor | tf.int32 | ||
ID | Text | tf.string | ||
Pronoun | Text | tf.string | ||
Pronoun-offset | Tensor | tf.int32 | ||
Text | Text | tf.string | ||
URL | Text | tf.string |
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):
- Citation:
@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}
}