Datasets:

Helsinki-NLP
/

multiun

	# 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.
	# See the License for the specific language governing permissions and
	# limitations under the License.
	"""MultiUN: Multilingual UN Parallel Text 2000—2009"""


	import itertools
	import os

	import datasets


	_CITATION = """\
	@inproceedings{eisele-chen-2010-multiun,
	title = "{M}ulti{UN}: A Multilingual Corpus from United Nation Documents",
	author = "Eisele, Andreas and
	Chen, Yu",
	booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
	month = may,
	year = "2010",
	address = "Valletta, Malta",
	publisher = "European Language Resources Association (ELRA)",
	url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/686_Paper.pdf",
	abstract = "This paper describes the acquisition, preparation and properties of a corpus extracted from the official documents of the United Nations (UN). This corpus is available in all 6 official languages of the UN, consisting of around 300 million words per language. We describe the methods we used for crawling, document formatting, and sentence alignment. This corpus also includes a common test set for machine translation. We present the results of a French-Chinese machine translation experiment performed on this corpus.",
	}

	@InProceedings{TIEDEMANN12.463,
	author = {J�rg Tiedemann},
	title = {Parallel Data, Tools and Interfaces in OPUS},
	booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
	year = {2012},
	month = {may},
	date = {23-25},
	address = {Istanbul, Turkey},
	editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
	publisher = {European Language Resources Association (ELRA)},
	isbn = {978-2-9517408-7-7},
	}
	"""


	_DESCRIPTION = """\
	This is a collection of translated documents from the United Nations. \
	This corpus is available in all 6 official languages of the UN, \
	consisting of around 300 million words per language
	"""


	_HOMEPAGE = "http://www.euromatrixplus.net/multi-un/"

	_LANGUAGES = ["ar", "de", "en", "es", "fr", "ru", "zh"]
	_LANGUAGE_PAIRS = list(itertools.combinations(_LANGUAGES, 2))

	_BASE_URL = "http://opus.nlpl.eu/download.php?f=MultiUN/v1/moses"
	_URLS = {f"{l1}-{l2}": f"{_BASE_URL}/{l1}-{l2}.txt.zip" for l1, l2 in _LANGUAGE_PAIRS}


	class UnMulti(datasets.GeneratorBasedBuilder):
	"""MultiUN: Multilingual UN Parallel Text 2000—2009"""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name=f"{l1}-{l2}", version=datasets.Version("1.0.0"), description=f"MultiUN {l1}-{l2}")
	for l1, l2 in _LANGUAGE_PAIRS
	]

	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."""
	lang_pair = self.config.name.split("-")
	data_dir = dl_manager.download_and_extract(_URLS[self.config.name])
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"source_file": os.path.join(data_dir, f"MultiUN.{self.config.name}.{lang_pair[0]}"),
	"target_file": os.path.join(data_dir, f"MultiUN.{self.config.name}.{lang_pair[1]}"),
	},
	),
	]

	def _generate_examples(self, source_file, target_file):
	source, target = tuple(self.config.name.split("-"))
	with open(source_file, encoding="utf-8") as src_f, open(target_file, encoding="utf-8") as tgt_f:
	for idx, (l1, l2) in enumerate(zip(src_f, tgt_f)):
	result = {"translation": {source: l1.strip(), target: l2.strip()}}
	yield idx, result