Datasets:
gap

	# coding=utf-8
	# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
	#
	# Licensed under the Apache License, Version 2.0 (the "License");
	# you may not use this file except in compliance with the License.
	# You may obtain a copy of the License at
	#
	# http://www.apache.org/licenses/LICENSE-2.0
	#
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	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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	# limitations under the License.

	# Lint as: python3
	"""GAP is a gender-balanced text data set."""


	import csv

	import datasets


	_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}
	}
	"""

	_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.
	"""

	_TRAINURL = "https://raw.githubusercontent.com/google-research-datasets/gap-coreference/master/gap-development.tsv"
	_VALIDATIONURL = "https://raw.githubusercontent.com/google-research-datasets/gap-coreference/master/gap-validation.tsv"
	_TESTURL = "https://raw.githubusercontent.com/google-research-datasets/gap-coreference/master/gap-test.tsv"


	class Gap(datasets.GeneratorBasedBuilder):
	"""GAP is a gender-balanced dataset.

	It contains 8,908 coreference-labeled pairs
	of (ambiguous pronoun, antecedent name), sampled from Wikipedia.
	"""

	VERSION = datasets.Version("0.1.0")

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"ID": datasets.Value("string"),
	"Text": datasets.Value("string"),
	"Pronoun": datasets.Value("string"),
	"Pronoun-offset": datasets.Value("int32"),
	"A": datasets.Value("string"),
	"A-offset": datasets.Value("int32"),
	"A-coref": datasets.Value("bool"),
	"B": datasets.Value("string"),
	"B-offset": datasets.Value("int32"),
	"B-coref": datasets.Value("bool"),
	"URL": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	homepage="https://github.com/google-research-datasets/gap-coreference",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	directory = dl_manager.download_and_extract(
	{"train": _TRAINURL, "validation": _VALIDATIONURL, "test": _TESTURL}
	)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"filepath": directory["train"]},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={"filepath": directory["validation"]},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": directory["test"]},
	),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as tsvfile:
	reader = csv.DictReader(tsvfile, dialect="excel-tab")
	for i, row in enumerate(reader):
	row["A-coref"] = row["A-coref"] == "TRUE"
	row["B-coref"] = row["B-coref"] == "TRUE"
	row["A-offset"] = int(row["A-offset"])
	row["B-offset"] = int(row["B-offset"])
	row["Pronoun-offset"] = int(row["Pronoun-offset"])
	yield i, row