@inproceedings{sohn-etal-2021-global,
title = "The Global Banking Standards {QA} Dataset ({GBS}-{QA})",
author = "Sohn, Kyunghwan and
Kwon, Sunjae and
Choi, Jaesik",
booktitle = "Proceedings of the Third Workshop on Economics and Natural Language Processing",
month = nov,
year = "2021",
address = "Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.econlp-1.3",
doi = "10.18653/v1/2021.econlp-1.3",
pages = "19--25",
abstract = "A domain specific question answering (QA) dataset dramatically improves the machine comprehension performance. This paper presents a new Global Banking Standards QA dataset (GBS-QA) in the banking regulation domain. The GBS-QA has three values. First, it contains actual questions from market players and answers from global rule setter, the Basel Committee on Banking Supervision (BCBS) in the middle of creating and revising banking regulations. Second, financial regulation experts analyze and verify pairs of questions and answers in the annotation process. Lastly, the GBS-QA is a totally different dataset with existing datasets in finance and is applicable to stimulate transfer learning research in the banking regulation domain.",
}
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<abstract>A domain specific question answering (QA) dataset dramatically improves the machine comprehension performance. This paper presents a new Global Banking Standards QA dataset (GBS-QA) in the banking regulation domain. The GBS-QA has three values. First, it contains actual questions from market players and answers from global rule setter, the Basel Committee on Banking Supervision (BCBS) in the middle of creating and revising banking regulations. Second, financial regulation experts analyze and verify pairs of questions and answers in the annotation process. Lastly, the GBS-QA is a totally different dataset with existing datasets in finance and is applicable to stimulate transfer learning research in the banking regulation domain.</abstract>
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%0 Conference Proceedings
%T The Global Banking Standards QA Dataset (GBS-QA)
%A Sohn, Kyunghwan
%A Kwon, Sunjae
%A Choi, Jaesik
%S Proceedings of the Third Workshop on Economics and Natural Language Processing
%D 2021
%8 nov
%I Association for Computational Linguistics
%C Punta Cana, Dominican Republic
%F sohn-etal-2021-global
%X A domain specific question answering (QA) dataset dramatically improves the machine comprehension performance. This paper presents a new Global Banking Standards QA dataset (GBS-QA) in the banking regulation domain. The GBS-QA has three values. First, it contains actual questions from market players and answers from global rule setter, the Basel Committee on Banking Supervision (BCBS) in the middle of creating and revising banking regulations. Second, financial regulation experts analyze and verify pairs of questions and answers in the annotation process. Lastly, the GBS-QA is a totally different dataset with existing datasets in finance and is applicable to stimulate transfer learning research in the banking regulation domain.
%R 10.18653/v1/2021.econlp-1.3
%U https://aclanthology.org/2021.econlp-1.3
%U https://doi.org/10.18653/v1/2021.econlp-1.3
%P 19-25
Markdown (Informal)
[The Global Banking Standards QA Dataset (GBS-QA)](https://aclanthology.org/2021.econlp-1.3) (Sohn et al., ECONLP 2021)
ACL
- Kyunghwan Sohn, Sunjae Kwon, and Jaesik Choi. 2021. The Global Banking Standards QA Dataset (GBS-QA). In Proceedings of the Third Workshop on Economics and Natural Language Processing, pages 19–25, Punta Cana, Dominican Republic. Association for Computational Linguistics.