Relationship Extraction Distant Supervised On
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P@10%
P@30%
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Modellname | P@10% | P@30% | Paper Title | Repository |
|---|---|---|---|---|
| PCNN | 61.3 | 46.5 | - | - |
| REDSandT | - | - | Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance Embeddings | - |
| RECON | 87.5 | 74.1 | RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network | - |
| KGPOOL | 92.3 | 86.7 | KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction | - |
| PCNN+ATT | 69.4 | 51.8 | - | - |
| BiGRU+WLA+EWA | - | - | Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning | - |
| CGRE | 84.5 | 71.5 | Distantly-Supervised Long-Tailed Relation Extraction Using Constraint Graphs | - |
| BGRU-SET | - | - | Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning | - |
| BGWA | 70.9 | 52.4 | Improving Distantly Supervised Relation Extraction using Word and Entity Based Attention | - |
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