2021
EMNLP
EMNLP 2021
The Global Banking Standards QA Dataset (GBS-QA)
Abstract
AbstractA 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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Interdisciplinary Bridge
- Artificial Intelligence and Natural Language Processing
Authors
Topics
Artificial Intelligence > Learning Paradigms > Transfer Learning
Natural Language Processing > Applications > Information Retrieval
Natural Language Processing > Applications > Question Answering
Machine Learning > Learning Types > Transfer Learning
Deep Learning > Learning Types > Domain Adaptation