INFOSYNC: Information Synchronization across Multilingual Semi-structured Tables

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

The First Workshop on Matching From Unstructured and Structured Data (MATCHING 2023) Long Paper

TLDR: Information Synchronization of semi-structured data across languages is challenging. For instance, Wikipedia tables in one language should be synchronized across languages. To address this problem, we introduce a new dataset INFOSYNC and a two-step method for tabular synchronization. INFOSYNC contai
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Abstract: Information Synchronization of semi-structured data across languages is challenging. For instance, Wikipedia tables in one language should be synchronized across languages. 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 The proposed method includes 1) Information Alignment to map rows and 2) Information Update for updating missing/outdated information for aligned tables across multilingual tables.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 603 table pairs. Our approach obtains an acceptance rate of 77.28% on Wikipedia, showing the effectiveness of the proposed method.