Datasets:
hrenwac_para

	# 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.
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	"""Croatian-English parallel corpus hrenWaC"""

	import datasets


	_CITATION = """
	@misc{11356/1058,
	title = {Croatian-English parallel corpus {hrenWaC} 2.0},
	author = {Ljube{\v s}i{\'c}, Nikola and Espl{\'a}-Gomis, Miquel and Ortiz Rojas, Sergio and Klubi{\v c}ka, Filip and Toral, Antonio},
	url = {http://hdl.handle.net/11356/1058},
	note = {Slovenian language resource repository {CLARIN}.{SI}},
	copyright = {{CLARIN}.{SI} User Licence for Internet Corpora},
	year = {2016} }
	"""

	_DESCRIPTION = """
	The hrenWaC corpus version 2.0 consists of parallel Croatian-English texts crawled from the .hr top-level domain for Croatia.
	The corpus was built with Spidextor (https://github.com/abumatran/spidextor), a tool that glues together the output of SpiderLing used for crawling and Bitextor used for bitext extraction. The accuracy of the extracted bitext on the segment level is around 80% and on the word level around 84%.
	"""

	_LICENSE = "CC BY-SA 3.0"

	_HOMEPAGE = "http://nlp.ffzg.hr/resources/corpora/hrenwac/"
	_URLS = "http://nlp.ffzg.hr/data/corpora/hrenwac/hrenwac.en-hr.txt.gz"


	class HrenwacPara(datasets.GeneratorBasedBuilder):
	"""Croatian-English parallel corpus hrenWaC"""

	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="hrenWaC",
	version=VERSION,
	description="The hrenWaC dataset.",
	),
	]

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features({"translation": datasets.features.Translation(languages=("en", "hr"))}),
	supervised_keys=("en", "hr"),
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	downloaded_file = dl_manager.download_and_extract({"train": _URLS})
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": downloaded_file["train"],
	},
	),
	]

	def _generate_examples(self, filepath):
	with open(filepath, encoding="utf8") as f:
	en = ""
	hr = ""
	i = -1
	for id_, row in enumerate(f):
	if id_ % 3 == 0:
	en = row.strip()
	if id_ % 3 == 1:
	hr = row.strip()
	if id_ % 3 == 2:
	i = i + 1
	yield i, {
	"translation": {
	"en": en,
	"hr": hr,
	}
	}