Datasets:
Tasks:
Translation
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translation
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# 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.
# See the License for the specific language governing permissions and
# 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
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