Datasets:
e2e_nlg_cleaned

	# coding=utf-8
	# Copyright 2020 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
	#
	# Unless required by applicable law or agreed to in writing, software
	# distributed under the License is distributed on an "AS IS" BASIS,
	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	# See the License for the specific language governing permissions and
	# limitations under the License.

	# Lint as: python3
	"""E2E Dataset: New Challenges For End-to-End Generation, cleaned version"""

	import csv

	import datasets


	_CITATION = """\
	@inproceedings{dusek-etal-2019-semantic,
	title = "Semantic Noise Matters for Neural Natural Language Generation",
	author = "Du{\v{s}}ek, Ond{\v{r}}ej and
	Howcroft, David M. and
	Rieser, Verena",
	booktitle = "Proceedings of the 12th International Conference on Natural Language Generation",
	month = oct # "{--}" # nov,
	year = "2019",
	address = "Tokyo, Japan",
	publisher = "Association for Computational Linguistics",
	url = "https://www.aclweb.org/anthology/W19-8652",
	doi = "10.18653/v1/W19-8652",
	pages = "421--426"
	}
	"""

	_DESCRIPTION = """\
	An update release of E2E NLG Challenge data with cleaned MRs and scripts, accompanying the following paper:

	Ondřej Dušek, David M. Howcroft, and Verena Rieser (2019): Semantic Noise Matters for Neural Natural Language Generation. In INLG, Tokyo, Japan.
	"""

	_URL = "https://github.com/tuetschek/e2e-cleaning/raw/master/cleaned-data/"
	_TRAINING_FILE = "train-fixed.no-ol.csv"
	_DEV_FILE = "devel-fixed.no-ol.csv"
	_TEST_FILE = "test-fixed.csv"

	_URLS = {
	"train": f"{_URL}{_TRAINING_FILE}",
	"dev": f"{_URL}{_DEV_FILE}",
	"test": f"{_URL}{_TEST_FILE}",
	}


	class E2eNLGCleaned(datasets.GeneratorBasedBuilder):
	"""E2E dataset, cleaned version."""

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"meaning_representation": datasets.Value("string"),
	"human_reference": datasets.Value("string"),
	}
	),
	supervised_keys=None,
	homepage="https://github.com/tuetschek/e2e-cleaning",
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	downloaded_files = dl_manager.download_and_extract(_URLS)

	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
	datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
	]

	def _generate_examples(self, filepath):
	with open(filepath, encoding="utf-8") as f:
	reader = csv.DictReader(f)
	for example_idx, example in enumerate(reader):
	yield example_idx, {
	"meaning_representation": example["mr"],
	"human_reference": example["ref"],
	}