Scaling Trust: Veracity-Driven Defect Detection in Entity Search
Veracity is a critical dimension of data quality that directly impacts a wide range of tasks. In entity search scenarios, Knowledge Graphs (KGs) such as DBpedia and Wikidata serve as core resources for accessing factual content. The veracity of these KGs is therefore essential for ensuring the reliability and trustworthiness of retrieved entities -- factors that directly influence user confidence in the search system. However, ensuring the truthfulness of entities remains a major challenge due to the complexities associated with the scale, development, and maintenance of KGs.
Authors
- Stefano Marchesin (ORCID: https://orcid.org/0000-0003-0362-5893)
- Ornella Irrera (ORCID: https://orcid.org/0000-0003-2284-5699)
- Omar Alonso (ORCID: https://orcid.org/0009-0009-2515-4771)
- Gianmaria Silvello (ORCID: https://orcid.org/0000-0003-4970-4554)
Institutions
- Amazon (United States) (US)
- University of Padua (IT)
Publication Details
- Published
- 2025-11-08
- DOI
- https://doi.org/10.1145/3746252.3761208
- Primary Topic
- Advanced Graph Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00