Datasets:
Tasks:
Translation
Multilinguality:
translation
Size Categories:
10K<n<100K
Language Creators:
found
Source Datasets:
original
Tags:
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. | |
"""SNOW T15 and T23: "Japanese Simplified Corpus with Core Vocabulary" and ''Crowdsourced Corpus of Sentence Simplification with Core Vocabulary".""" | |
import openpyxl # noqa: requires this pandas optional dependency for reading xlsx files | |
import pandas as pd | |
import datasets | |
_CITATION = """\ | |
@inproceedings{maruyama-yamamoto-2018-simplified, | |
title = "Simplified Corpus with Core Vocabulary", | |
author = "Maruyama, Takumi and | |
Yamamoto, Kazuhide", | |
booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)", | |
month = may, | |
year = "2018", | |
address = "Miyazaki, Japan", | |
publisher = "European Language Resources Association (ELRA)", | |
url = "https://www.aclweb.org/anthology/L18-1185", | |
} | |
@inproceedings{yamamoto-2017-simplified-japanese, | |
title = "やさしい⽇本語対訳コーパスの構築", | |
author = "⼭本 和英 and | |
丸⼭ 拓海 and | |
⾓張 ⻯晴 and | |
稲岡 夢⼈ and | |
⼩川 耀⼀朗 and | |
勝⽥ 哲弘 and | |
髙橋 寛治", | |
booktitle = "言語処理学会第23回年次大会", | |
month = 3月, | |
year = "2017", | |
address = "茨城, 日本", | |
publisher = "言語処理学会", | |
url = "https://www.anlp.jp/proceedings/annual_meeting/2017/pdf_dir/B5-1.pdf", | |
} | |
@inproceedings{katsuta-yamamoto-2018-crowdsourced, | |
title = "Crowdsourced Corpus of Sentence Simplification with Core Vocabulary", | |
author = "Katsuta, Akihiro and | |
Yamamoto, Kazuhide", | |
booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)", | |
month = may, | |
year = "2018", | |
address = "Miyazaki, Japan", | |
publisher = "European Language Resources Association (ELRA)", | |
url = "https://www.aclweb.org/anthology/L18-1072", | |
} | |
""" | |
_DESCRIPTION = """\ | |
About SNOW T15: \ | |
The simplified corpus for the Japanese language. The corpus has 50,000 manually simplified and aligned sentences. \ | |
This corpus contains the original sentences, simplified sentences and English translation of the original sentences. \ | |
It can be used for automatic text simplification as well as translating simple Japanese into English and vice-versa. \ | |
The core vocabulary is restricted to 2,000 words where it is selected by accounting for several factors such as meaning preservation, variation, simplicity and the UniDic word segmentation criterion. | |
For details, refer to the explanation page of Japanese simplification (http://www.jnlp.org/research/Japanese_simplification). \ | |
The original texts are from "small_parallel_enja: 50k En/Ja Parallel Corpus for Testing SMT Methods", which is a bilingual corpus for machine translation. \ | |
\ | |
About SNOW T23: \ | |
An expansion corpus of 35,000 sentences rewritten in easy Japanese (simple Japanese vocabulary) based on SNOW T15. \ | |
The original texts are from "Tanaka Corpus" (http://www.edrdg.org/wiki/index.php/Tanaka_Corpus). | |
""" | |
_HOMEPAGE = "http://www.jnlp.org/SNOW/T15, http://www.jnlp.org/SNOW/T23" | |
_LICENSE = "CC BY 4.0" | |
# The HuggingFace dataset library don't host the datasets but only point to the original files | |
_URLs = { | |
"snow_t15": "https://filedn.com/lit4DCIlHwxfS1gj9zcYuDJ/SNOW/T15-2020.1.7.xlsx", | |
"snow_t23": "https://filedn.com/lit4DCIlHwxfS1gj9zcYuDJ/SNOW/T23-2020.1.7.xlsx", | |
} | |
class SnowSimplifiedJapaneseCorpus(datasets.GeneratorBasedBuilder): | |
"""SNOW T15 and T23: "Japanese Simplified Corpus with Core Vocabulary" and ''Crowdsourced Corpus of Sentence Simplification with Core Vocabulary".""" | |
VERSION = datasets.Version("1.1.0") | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig(name="snow_t15", version=VERSION, description="SNOW T15 dataset"), | |
datasets.BuilderConfig(name="snow_t23", version=VERSION, description="SNOW T23 dataset (extension)"), | |
] | |
DEFAULT_CONFIG_NAME = "snow_t15" | |
def _info(self): | |
if self.config.name == "snow_t15": | |
features = datasets.Features( | |
{ | |
"ID": datasets.Value("string"), | |
"original_ja": datasets.Value("string"), | |
"simplified_ja": datasets.Value("string"), | |
"original_en": datasets.Value("string"), | |
} | |
) | |
else: | |
features = datasets.Features( | |
{ | |
"ID": datasets.Value("string"), | |
"original_ja": datasets.Value("string"), | |
"simplified_ja": datasets.Value("string"), | |
"original_en": datasets.Value("string"), | |
"proper_noun": 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.""" | |
my_urls = _URLs[self.config.name] | |
data_url = dl_manager.download(my_urls) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={"filepath": data_url, "split": "train"}, | |
), | |
] | |
def _generate_examples(self, filepath, split): | |
"""Yields examples.""" | |
with open(filepath, "rb") as f: | |
df = pd.read_excel(f, engine="openpyxl").astype("str") | |
if self.config.name == "snow_t15": | |
for id_, row in df.iterrows(): | |
yield id_, { | |
"ID": row["ID"], | |
"original_ja": row["#日本語(原文)"], | |
"simplified_ja": row["#やさしい日本語"], | |
"original_en": row["#英語(原文)"], | |
} | |
else: | |
for id_, row in df.iterrows(): | |
yield id_, { | |
"ID": row["ID"], | |
"original_ja": row["#日本語(原文)"], | |
"simplified_ja": row["#やさしい日本語"], | |
"original_en": row["#英語(原文)"], | |
"proper_noun": row["#固有名詞"], | |
} | |