InfoSync: Information Synchronization across Multilingual Semi-structured Tables

Siddharth Khincha, Chelsi Jain, Vivek Gupta, Tushar Kataria, Shuo Zhang


Abstract
Information Synchronization of semi-structured data across languages is challenging. For example, Wikipedia tables in one language need to be synchronized with others. To address this problem, we introduce a new dataset InfoSync and a two-step method for tabular synchronization. InfoSync contains 100K entity-centric tables (Wikipedia Infoboxes) across 14 languages, of which a subset (~3.5K pairs) are manually annotated. The proposed method includes 1) Information Alignment to map rows and 2) Information Update for updating missing/outdated information for aligned tables across multilingual tables. When evaluated on InfoSync, information alignment achieves an F1 score of 87.91 (en <-> non-en). To evaluate information updation, we perform human-assisted Wikipedia edits on Infoboxes for 532 table pairs. Our approach obtains an acceptance rate of 77.28% on Wikipedia, showing the effectiveness of the proposed method.
Anthology ID:
2023.findings-acl.159
Volume:
Findings of the Association for Computational Linguistics: ACL 2023
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2536–2559
Language:
URL:
https://aclanthology.org/2023.findings-acl.159
DOI:
10.18653/v1/2023.findings-acl.159
Bibkey:
Cite (ACL):
Siddharth Khincha, Chelsi Jain, Vivek Gupta, Tushar Kataria, and Shuo Zhang. 2023. InfoSync: Information Synchronization across Multilingual Semi-structured Tables. In Findings of the Association for Computational Linguistics: ACL 2023, pages 2536–2559, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
InfoSync: Information Synchronization across Multilingual Semi-structured Tables (Khincha et al., Findings 2023)
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PDF:
https://aclanthology.org/2023.findings-acl.159.pdf
Video:
 https://aclanthology.org/2023.findings-acl.159.mp4