Tracing Organisation Evolution in Wikidata

Marieke van Erp, Jiaqi Zhu, Vera Provatorova


Abstract
37 Entities change over time, and while information about entity change is contained in knowledge graphs (KGs), it is often not stated explicitly. This makes KGs less useful for investigating entities over time, or downstream tasks such as historical entity linking. In this paper, we present an approach and experiments that make explicit entity change in Wikidata. Our contributions are a mapping between an existing change ontology and Wikidata properties to identify types of change, and a dataset of entities with explicit evolution information and analytics on this dataset.
Anthology ID:
2025.ldk-1.9
Volume:
Proceedings of the 5th Conference on Language, Data and Knowledge
Month:
September
Year:
2025
Address:
Naples, Italy
Editors:
Mehwish Alam, Andon Tchechmedjiev, Jorge Gracia, Dagmar Gromann, Maria Pia di Buono, Johanna Monti, Maxim Ionov
Venues:
LDK | WS
SIG:
Publisher:
Unior Press
Note:
Pages:
76–86
Language:
URL:
https://preview.aclanthology.org/ldl-25-ingestion/2025.ldk-1.9/
DOI:
Bibkey:
Cite (ACL):
Marieke van Erp, Jiaqi Zhu, and Vera Provatorova. 2025. Tracing Organisation Evolution in Wikidata. In Proceedings of the 5th Conference on Language, Data and Knowledge, pages 76–86, Naples, Italy. Unior Press.
Cite (Informal):
Tracing Organisation Evolution in Wikidata (van Erp et al., LDK 2025)
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PDF:
https://preview.aclanthology.org/ldl-25-ingestion/2025.ldk-1.9.pdf