ACL 2023findings4 citations

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 The proposed method includes 1) Information Alignment to map rows and 2) Information Update for updating missing/outdated information for aligned tables across multilingual tables.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.

BibTeX
@inproceedings{khincha-etal-2023-infosync,
    title = "{I}nfo{S}ync: Information Synchronization across Multilingual Semi-structured Tables",
    author = "Khincha, Siddharth  and
      Jain, Chelsi  and
      Gupta, Vivek  and
      Kataria, Tushar  and
      Zhang, Shuo",
    editor = "Rogers, Anna  and
      Boyd-Graber, Jordan  and
      Okazaki, Naoaki",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.159/",
    doi = "10.18653/v1/2023.findings-acl.159",
    pages = "2536--2559"
}