Cell Entity Annotation On Toughtables Dbp
Metrics
F1 (%)
Results
Performance results of various models on this benchmark
Model Name | F1 (%) | Paper Title | Repository |
|---|---|---|---|
| Kepler-aSI | 50.9 | Kepler-aSI at SemTab 2021 | - |
| KGCODE-Tab | 82.7 | KGCODE-Tab Results for SemTab 2022 | - |
| DAGOBAH | 94.5 | DAGOBAH: Table and Graph Contexts for Efficient Semantic Annotation of Tabular Data | - |
| MAGIC | 18.4 | MAGIC: Mining an Augmented Graph using INK, starting from a CSV | |
| JenTab | 60.7 | JenTab Meets SemTab 2021's New Challenges |
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