The Global Banking Standards QA Dataset (GBS-QA)

Kyunghwan Sohn, Sunjae Kwon, Jaesik Choi


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.
Anthology ID:
2021.econlp-1.3
Volume:
Proceedings of the Third Workshop on Economics and Natural Language Processing
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Venues:
ECONLP | EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
19–25
Language:
URL:
https://aclanthology.org/2021.econlp-1.3
DOI:
10.18653/v1/2021.econlp-1.3
Bibkey:
Cite (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.
Cite (Informal):
The Global Banking Standards QA Dataset (GBS-QA) (Sohn et al., ECONLP 2021)
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PDF:
https://aclanthology.org/2021.econlp-1.3.pdf