2025 continues the mission of benchmarking semantic table interpretation systems in an era shaped by large language models (LLMs) and retrieval-augmented strategies. This edition introduces two complementary tracks. The first is the large-scale MammoTab dataset for cell entity annotation (CEA) aligned to Wikidata. The second is the new Secu-Table Track designed to evaluate robustness under noisy, adversarial, and security-domain table conditions. This paper presents an overview of the challenge setup, datasets, evaluation methodology, and the key outcomes of this edition.
Hassanzadeh, O., Cremaschi, M., D'Adda, F., Azanzi, F., Bikim, J., Jimenez-Ruiz, E. (2025). Results of SemTab 2025. In Proceedings of the 20th International Workshop on Ontology Matching co-located with the 24th International Semantic Web Conference (ISWC 2025) (pp.216-220). CEUR-WS.
Results of SemTab 2025
Cremaschi M.;
2025
Abstract
2025 continues the mission of benchmarking semantic table interpretation systems in an era shaped by large language models (LLMs) and retrieval-augmented strategies. This edition introduces two complementary tracks. The first is the large-scale MammoTab dataset for cell entity annotation (CEA) aligned to Wikidata. The second is the new Secu-Table Track designed to evaluate robustness under noisy, adversarial, and security-domain table conditions. This paper presents an overview of the challenge setup, datasets, evaluation methodology, and the key outcomes of this edition.
| File | Dimensione | Formato | |
|---|---|---|---|
|
Hassanzadeh et al-2025-Ontology Matching-CEUR-VoR.pdf
accesso aperto
Tipologia di allegato:
Publisher’s Version (Version of Record, VoR)
Licenza:
Creative Commons
Dimensione
1.17 MB
Formato
Adobe PDF
|
1.17 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
