Datasets:

Helsinki-NLP
/

bianet

	# 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.
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	#
	# http://www.apache.org/licenses/LICENSE-2.0
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	# distributed under the License is distributed on an "AS IS" BASIS,
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	# limitations under the License.
	"""Bianet: A parallel news corpus in Turkish, Kurdish and English"""


	import os

	import datasets


	_CITATION = """\
	@InProceedings{ATAMAN18.6,
	author = {Duygu Ataman},
	title = {Bianet: A Parallel News Corpus in Turkish, Kurdish and English},
	booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
	year = {2018},
	month = {may},
	date = {7-12},
	location = {Miyazaki, Japan},
	editor = {Jinhua Du and Mihael Arcan and Qun Liu and Hitoshi Isahara},
	publisher = {European Language Resources Association (ELRA)},
	address = {Paris, France},
	isbn = {979-10-95546-15-3},
	language = {english}
	}"""

	_HOMEPAGE = "http://opus.nlpl.eu/Bianet.php"


	_LICENSE = "CC-BY-SA-4.0"

	_VALID_LANGUAGE_PAIRS = {
	("en", "ku"): "http://opus.nlpl.eu/download.php?f=Bianet/v1/moses/en-ku.txt.zip",
	("en", "tr"): "http://opus.nlpl.eu/download.php?f=Bianet/v1/moses/en-tr.txt.zip",
	("ku", "tr"): "http://opus.nlpl.eu/download.php?f=Bianet/v1/moses/ku-tr.txt.zip",
	}

	_VERSION = "1.0.0"

	_DESCRIPTION = """\
	A parallel news corpus in Turkish, Kurdish and English.
	Bianet collects 3,214 Turkish articles with their sentence-aligned Kurdish or English translations from the Bianet online newspaper.
	3 languages, 3 bitexts
	total number of files: 6
	total number of tokens: 2.25M
	total number of sentence fragments: 0.14M
	"""

	_BASE_NAME = "Bianet.{}-{}.{}"


	class BianetConfig(datasets.BuilderConfig):
	"""BuilderConfig for Bianet: A parallel news corpus in Turkish, Kurdish and English"""

	def __init__(self, language_pair=(None, None), **kwargs):
	"""BuilderConfig for Bianet: A parallel news corpus in Turkish, Kurdish and English.
	The first language in `language_pair` should consist of two strings joined by
	an underscore (e.g. "en-tr").
	Args:
	language_pair: pair of languages that will be used for translation.
	**kwargs: keyword arguments forwarded to super.
	"""
	name = "%s_to_%s" % (language_pair[0], language_pair[1])

	description = ("Translation dataset from %s to %s or %s to %s.") % (
	language_pair[0],
	language_pair[1],
	language_pair[1],
	language_pair[0],
	)
	super(BianetConfig, self).__init__(
	name=name, description=description, version=datasets.Version(_VERSION, ""), **kwargs
	)

	# Validate language pair.
	assert language_pair in _VALID_LANGUAGE_PAIRS, (
	"Config language pair (%s, " "%s) not supported"
	) % language_pair

	self.language_pair = language_pair


	class Bianet(datasets.GeneratorBasedBuilder):

	BUILDER_CONFIGS = [
	BianetConfig(
	language_pair=pair,
	)
	for pair in _VALID_LANGUAGE_PAIRS.keys()
	]

	BUILDER_CONFIG_CLASS = BianetConfig

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

	def _split_generators(self, dl_manager):
	download_url = _VALID_LANGUAGE_PAIRS.get(tuple(self.config.language_pair))
	path = dl_manager.download_and_extract(download_url)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"datapath": path},
	)
	]

	def _generate_examples(self, datapath):
	lang1, lang2 = self.config.language_pair
	lang1_file = _BASE_NAME.format(lang1, lang2, lang1)
	lang2_file = _BASE_NAME.format(lang1, lang2, lang2)
	lang1_path = os.path.join(datapath, lang1_file)
	lang2_path = os.path.join(datapath, lang2_file)

	with open(lang1_path, encoding="utf-8") as f1, open(lang2_path, encoding="utf-8") as f2:
	for sentence_counter, (x, y) in enumerate(zip(f1, f2)):
	x = x.strip()
	y = y.strip()
	result = (
	sentence_counter,
	{
	"id": str(sentence_counter),
	"translation": {lang1: x, lang2: y},
	},
	)
	yield result