metadata

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

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。オリジナルのリポジトリで公開されているデータセットを利用しています。

Licence

コードのライセンスは Creative Commons Attribution-ShareAlike 4.0 International License です。データそのもののライセンスは配布元のライセンスに従ってください。

Citation

@inproceedings{kurihara-etal-2022-jglue,
    title = "{JGLUE}: {J}apanese General Language Understanding Evaluation",
    author = "Kurihara, Kentaro  and
      Kawahara, Daisuke  and
      Shibata, Tomohide",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.317",
    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.",
}

@InProceedings{Kurihara_nlp2022,
  author = 	"栗原健太郎 and 河原大輔 and 柴田知秀",
  title = 	"JGLUE: 日本語言語理解ベンチマーク",
  booktitle = 	"言語処理学会第 28 回年次大会",
  year =	"2022",
  url = "https://www.anlp.jp/proceedings/annual_meeting/2022/pdf_dir/E8-4.pdf"
  note= "in Japanese"
}

Contributions

データセット作成者である Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata に感謝を申し上げます。また本リポジトリのコードは Shunsuke Kitadaのこちらのリポジトリを基に作成されたものです。