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# 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
"""
# Original:
# _HOMEPAGE = "http://www.euromatrixplus.net/multi-un/"
_HOMEPAGE = "https://opus.nlpl.eu/MultiUN/corpus/version/MultiUN"
_LANGUAGES = ["ar", "de", "en", "es", "fr", "ru", "zh"]
_LANGUAGE_PAIRS = list(itertools.combinations(_LANGUAGES, 2))
_BASE_URL = "https://object.pouta.csc.fi/OPUS-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
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