|
--- |
|
annotations_creators: |
|
- crowdsourced |
|
language: |
|
- ja |
|
language_creators: |
|
- crowdsourced |
|
- found |
|
license: |
|
- cc-by-4.0 |
|
multilinguality: |
|
- monolingual |
|
pretty_name: JGLUE |
|
size_categories: [] |
|
source_datasets: |
|
- original |
|
tags: |
|
- MARC |
|
- STS |
|
- NLI |
|
- SQuAD |
|
- CommonsenseQA |
|
task_categories: |
|
- multiple-choice |
|
- question-answering |
|
- sentence-similarity |
|
- text-classification |
|
task_ids: |
|
- multiple-choice-qa |
|
- open-domain-qa |
|
- multi-class-classification |
|
- sentiment-classification |
|
--- |
|
|
|
# Dataset Card for JGLUE |
|
|
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[](https://aclanthology.org/2022.lrec-1.317) |
|
|
|
書籍『大規模言語モデル入門』で使用する、JGLUEのデータセットです。 |
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[オリジナルのリポジトリ](https://github.com/yahoojapan/JGLUE)で公開されているデータセットを利用しています。 |
|
|
|
|
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### Licence |
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コードのライセンスは Creative Commons Attribution-ShareAlike 4.0 International License です。 |
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データそのもののライセンスは[配布元](https://github.com/yahoojapan/JGLUE)のライセンスに従ってください。 |
|
|
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### Citation |
|
|
|
```bibtex |
|
@inproceedings{kurihara-etal-2022-jglue, |
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title = "{JGLUE}: {J}apanese General Language Understanding Evaluation", |
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author = "Kurihara, Kentaro and |
|
Kawahara, Daisuke and |
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Shibata, Tomohide", |
|
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference", |
|
month = jun, |
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year = "2022", |
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address = "Marseille, France", |
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publisher = "European Language Resources Association", |
|
url = "https://aclanthology.org/2022.lrec-1.317", |
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pages = "2957--2966", |
|
abstract = "To develop high-performance natural language understanding (NLU) models, it is necessary to have a benchmark to evaluate and analyze NLU ability from various perspectives. While the English NLU benchmark, GLUE, has been the forerunner, benchmarks are now being released for languages other than English, such as CLUE for Chinese and FLUE for French; but there is no such benchmark for Japanese. We build a Japanese NLU benchmark, JGLUE, from scratch without translation to measure the general NLU ability in Japanese. We hope that JGLUE will facilitate NLU research in Japanese.", |
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} |
|
``` |
|
|
|
```bibtex |
|
@InProceedings{Kurihara_nlp2022, |
|
author = "栗原健太郎 and 河原大輔 and 柴田知秀", |
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title = "JGLUE: 日本語言語理解ベンチマーク", |
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booktitle = "言語処理学会第 28 回年次大会", |
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year = "2022", |
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url = "https://www.anlp.jp/proceedings/annual_meeting/2022/pdf_dir/E8-4.pdf" |
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note= "in Japanese" |
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} |
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``` |
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|
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### Contributions |
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データセット作成者である [Kentaro Kurihara](https://twitter.com/kkurihara_cs), [Daisuke Kawahara](https://twitter.com/daisukekawahar1), [Tomohide Shibata](https://twitter.com/stomohide) に感謝を申し上げます。 |
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また本リポジトリのコードは [Shunsuke Kitada](https://twitter.com/shunk031)の[こちらのリポジトリ](https://huggingface.co/datasets/shunk031/JGLUE)を基に作成されたものです。 |
