Datasets:
eu_regulatory_ir

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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.
	"""EURegIR: Regulatory Compliance IR (EU/UK)"""


	import json
	import os

	import datasets


	_CITATION = """\
	@inproceedings{chalkidis-etal-2021-regir,
	title = "Regulatory Compliance through Doc2Doc Information Retrieval: A case study in EU/UK legislation where text similarity has limitations",
	author = "Chalkidis, Ilias and Fergadiotis, Emmanouil and Manginas, Nikos and Katakalou, Eva, and Malakasiotis, Prodromos",
	booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2021)",
	year = "2021",
	address = "Online",
	publisher = "Association for Computational Linguistics",
	url = "https://arxiv.org/abs/2101.10726",
	}
	"""

	_DESCRIPTION = """\
	EURegIR: Regulatory Compliance IR (EU/UK)
	"""

	_HOMEPAGE = "https://archive.org/details/eacl2021_regir_dataset"

	_LICENSE = "CC BY-SA (Creative Commons / Attribution-ShareAlike)"

	_URLs = {
	"eu2uk": "https://archive.org/download/eacl2021_regir_datasets/eu2uk.zip",
	"uk2eu": "https://archive.org/download/eacl2021_regir_datasets/uk2eu.zip",
	}


	class EuRegulatoryIr(datasets.GeneratorBasedBuilder):
	"""EURegIR: Regulatory Compliance IR (EU/UK)"""

	VERSION = datasets.Version("1.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="eu2uk", version=VERSION, description="EURegIR: Regulatory Compliance IR (EU2UK)"),
	datasets.BuilderConfig(name="uk2eu", version=VERSION, description="EURegIR: Regulatory Compliance IR (UK2EU)"),
	]

	def _info(self):
	if self.config.name == "eu2uk":
	features = datasets.Features(
	{
	"document_id": datasets.Value("string"),
	"publication_year": datasets.Value("string"),
	"text": datasets.Value("string"),
	"relevant_documents": datasets.features.Sequence(datasets.Value("string")),
	}
	)
	else:
	features = datasets.Features(
	{
	"document_id": datasets.Value("string"),
	"publication_year": datasets.Value("string"),
	"text": datasets.Value("string"),
	"relevant_documents": datasets.features.Sequence(datasets.Value("string")),
	}
	)
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage=_HOMEPAGE,
	# License for the dataset if available
	license=_LICENSE,
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	my_urls = _URLs[self.config.name]
	data_dir = dl_manager.download_and_extract(my_urls)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": os.path.join(data_dir, "train.jsonl"),
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl"), "split": "test"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": os.path.join(data_dir, "dev.jsonl"),
	"split": "dev",
	},
	),
	datasets.SplitGenerator(
	name=f"{self.config.name.split('2')[1]}_corpus",
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": os.path.join(data_dir, "corpus.jsonl"),
	"split": f"{self.config.name.split('2')[1]}_corpus",
	},
	),
	]

	def _generate_examples(
	self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	):
	"""Yields examples as (key, example) tuples."""
	# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
	# The `key` is here for legacy reason (tfds) and is not important in itself.

	with open(filepath, encoding="utf-8") as f:
	for id_, row in enumerate(f):
	data = json.loads(row)
	yield id_, {
	"document_id": data["document_id"],
	"text": data["text"],
	"publication_year": data["publication_year"],
	"relevant_documents": data["relevant_documents"]
	if split != f"{self.config.name.split('2')[1]}_corpus"
	else [],
	}