Datasets:
Tasks:
Translation
Multilinguality:
translation
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
# 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. | |
"""Japanese-English Business Scene Dialogue (BSD) dataset. """ | |
from __future__ import absolute_import, division, print_function | |
import json | |
import datasets | |
_CITATION = """\ | |
@inproceedings{rikters-etal-2019-designing, | |
title = "Designing the Business Conversation Corpus", | |
author = "Rikters, Matīss and | |
Ri, Ryokan and | |
Li, Tong and | |
Nakazawa, Toshiaki", | |
booktitle = "Proceedings of the 6th Workshop on Asian Translation", | |
month = nov, | |
year = "2019", | |
address = "Hong Kong, China", | |
publisher = "Association for Computational Linguistics", | |
url = "https://www.aclweb.org/anthology/D19-5204", | |
doi = "10.18653/v1/D19-5204", | |
pages = "54--61" | |
} | |
""" | |
_DESCRIPTION = """\ | |
This is the Business Scene Dialogue (BSD) dataset, | |
a Japanese-English parallel corpus containing written conversations | |
in various business scenarios. | |
The dataset was constructed in 3 steps: | |
1) selecting business scenes, | |
2) writing monolingual conversation scenarios according to the selected scenes, and | |
3) translating the scenarios into the other language. | |
Half of the monolingual scenarios were written in Japanese | |
and the other half were written in English. | |
Fields: | |
- id: dialogue identifier | |
- no: sentence pair number within a dialogue | |
- en_speaker: speaker name in English | |
- ja_speaker: speaker name in Japanese | |
- en_sentence: sentence in English | |
- ja_sentence: sentence in Japanese | |
- original_language: language in which monolingual scenario was written | |
- tag: scenario | |
- title: scenario title | |
""" | |
_HOMEPAGE = "https://github.com/tsuruoka-lab/BSD" | |
_LICENSE = "CC BY-NC-SA 4.0" | |
_REPO = "https://raw.githubusercontent.com/tsuruoka-lab/BSD/master/" | |
_URLs = { | |
"train": _REPO + "train.json", | |
"dev": _REPO + "dev.json", | |
"test": _REPO + "test.json", | |
} | |
class BsdJaEn(datasets.GeneratorBasedBuilder): | |
"""Japanese-English Business Scene Dialogue (BSD) dataset. """ | |
VERSION = datasets.Version("1.0.0") | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"tag": datasets.Value("string"), | |
"title": datasets.Value("string"), | |
"original_language": datasets.Value("string"), | |
"no": datasets.Value("int32"), | |
"en_speaker": datasets.Value("string"), | |
"ja_speaker": datasets.Value("string"), | |
"en_sentence": datasets.Value("string"), | |
"ja_sentence": datasets.Value("string"), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage=_HOMEPAGE, | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
data_dir = dl_manager.download_and_extract(_URLs) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": data_dir["train"], | |
"split": "train", | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={"filepath": data_dir["test"], "split": "test"}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepath": data_dir["dev"], | |
"split": "dev", | |
}, | |
), | |
] | |
def _generate_examples(self, filepath, split): | |
""" Yields examples. """ | |
with open(filepath, encoding="utf-8") as f: | |
data = json.load(f) | |
for dialogue in data: | |
id_ = dialogue["id"] | |
tag = dialogue["tag"] | |
title = dialogue["title"] | |
original_language = dialogue["original_language"] | |
conversation = dialogue["conversation"] | |
for turn in conversation: | |
sent_no = int(turn["no"]) | |
en_speaker = turn["en_speaker"] | |
ja_speaker = turn["ja_speaker"] | |
en_sentence = turn["en_sentence"] | |
ja_sentence = turn["ja_sentence"] | |
yield id_, { | |
"id": id_, | |
"tag": tag, | |
"title": title, | |
"original_language": original_language, | |
"no": sent_no, | |
"en_speaker": en_speaker, | |
"ja_speaker": ja_speaker, | |
"en_sentence": en_sentence, | |
"ja_sentence": ja_sentence, | |
} | |