Cell Entity Annotation On Toughtables Wd
Metrics
F1 (%)
Results
Performance results of various models on this benchmark
Model Name | F1 (%) | Paper Title | Repository |
|---|---|---|---|
| Kepler-aSI | 62 | Kepler-aSI at SemTab 2021 | - |
| JenTab | 45.7 | JenTab Meets SemTab 2021's New Challenges | |
| DAGOBAH | 92.3 | DAGOBAH: Table and Graph Contexts for Efficient Semantic Annotation of Tabular Data | - |
| s-elBat | 93.8 | Results of SemTab 2022 | - |
| DAGOBAH | 94.5 | From Heuristics to Language Models: A Journey Through the Universe of Semantic Table Interpretation with DAGOBAH | - |
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