Datasets:
scielo

	# coding=utf-8
	# Copyright 2020 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
	#
	# 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.
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	"""Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO"""


	import datasets


	_CITATION = """\
	@inproceedings{soares2018large,
	title={A Large Parallel Corpus of Full-Text Scientific Articles},
	author={Soares, Felipe and Moreira, Viviane and Becker, Karin},
	booktitle={Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC-2018)},
	year={2018}
	}
	"""


	_DESCRIPTION = """\
	A parallel corpus of full-text scientific articles collected from Scielo database in the following languages: \
	English, Portuguese and Spanish. The corpus is sentence aligned for all language pairs, \
	as well as trilingual aligned for a small subset of sentences. Alignment was carried out using the Hunalign algorithm.
	"""


	_HOMEPAGE = "https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB"

	_LANGUAGES = ["en-es", "en-pt", "en-pt-es"]

	_URLS = {
	"en-es": "https://ndownloader.figstatic.com/files/14019287",
	"en-pt": "https://ndownloader.figstatic.com/files/14019308",
	"en-pt-es": "https://ndownloader.figstatic.com/files/14019293",
	}


	class Scielo(datasets.GeneratorBasedBuilder):
	"""Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO"""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="en-es", version=datasets.Version("1.0.0"), description="English-Spanish"),
	datasets.BuilderConfig(name="en-pt", version=datasets.Version("1.0.0"), description="English-Portuguese"),
	datasets.BuilderConfig(
	name="en-pt-es", version=datasets.Version("1.0.0"), description="English-Portuguese-Spanish"
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{"translation": datasets.features.Translation(languages=tuple(self.config.name.split("-")))}
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	archive = dl_manager.download(_URLS[self.config.name])
	lang_pair = self.config.name.split("-")
	fname = self.config.name.replace("-", "_")

	if self.config.name == "en-pt-es":
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"source_file": f"{fname}.en",
	"target_file": f"{fname}.pt",
	"target_file_2": f"{fname}.es",
	"files": dl_manager.iter_archive(archive),
	},
	),
	]

	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"source_file": f"{fname}.{lang_pair[0]}",
	"target_file": f"{fname}.{lang_pair[1]}",
	"files": dl_manager.iter_archive(archive),
	},
	),
	]

	def _generate_examples(self, source_file, target_file, files, target_file_2=None):
	for path, f in files:
	if path == source_file:
	source_sentences = f.read().decode("utf-8").split("\n")
	elif path == target_file:
	target_sentences = f.read().decode("utf-8").split("\n")
	elif self.config.name == "en-pt-es" and path == target_file_2:
	target_sentences_2 = f.read().decode("utf-8").split("\n")

	if self.config.name == "en-pt-es":
	source, target, target_2 = tuple(self.config.name.split("-"))
	for idx, (l1, l2, l3) in enumerate(zip(source_sentences, target_sentences, target_sentences_2)):
	result = {"translation": {source: l1, target: l2, target_2: l3}}
	yield idx, result
	else:
	source, target = tuple(self.config.name.split("-"))
	for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)):
	result = {"translation": {source: l1, target: l2}}
	yield idx, result