SemTab: Semantic Web Challenge on Tabular Data to Knowledge Graph Matching
This challenge aims at benchmarking systems dealing with the tabular data to KG matching problem, so as to
facilitate their comparison on the same basis and the reproducibility of the results.
Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen, Kavitha Srinivas and Vincenzo Cutrona.
Results of SemTab 2020. Vol-2775 of CEUR Workshop Proceedings. 2020.
Ernesto Jiménez-Ruiz, Oktie Hassanzadeh, Vasilis Efthymiou, Jiaoyan Chen and Kavitha Srinivas.
SemTab 2019: Resources to Benchmark Tabular Data to Knowledge Graph Matching Systems. Extended Semantic Web Conference (ESWC). 2020.
Vincenzo Cutrona, Federico Bianchi, Ernesto Jiménez-Ruiz and Matteo Palmonari.
Tough Tables: Carefully Evaluating Entity Linking for Tabular Data. International Semantic Web Conference (ISWC). 2020.
- Madelon Hulsebos, Çagatay Demiralp, Paul Groth: GitTables: A Large-Scale Corpus of Relational Tables.
CoRR abs/2106.07258. 2021. [Paper]
- Nora Abdelmageed, Sirko Schindler and Birgitta König-Ries. BiodivTab: A Table Annotation Benchmark based on Biodiversity Research Data.
SemTab 2021 proceedings (to appear). CEUR Workshop Proceedings.
The challenge has been supported by the AIDA project,
the SIRIUS Centre for Research-driven Innovation, and IBM Research.
We would like to thank the challenge participants, the ISWC & OM organisers, and the AIcrowd team for their contribution to the success of SemTab.
We would also like to acknowledge that the work of the challenge organisers was greatly simplified by using the EasyChair conference management system and
the CEUR open-access publication service.