Link Prediction On Umls
Metriken
Hits@10
MR
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | Hits@10 | MR |
|---|---|---|
| joint-language-semantic-and-structure | 0.994 | 1.39 |
| palt-parameter-lite-transfer-of-language | 0.990 | 1.57 |
| embedding-entities-and-relations-for-learning | 0.846 | 5.52 |
| convolutional-2d-knowledge-graph-embeddings | 0.990 | 1.51 |
| semantic-triple-encoder-for-fast-open-set | 0.991 | 1.49 |
| complex-embeddings-for-simple-link-prediction | 0.967 | 2.59 |
| kglm-integrating-knowledge-graph-structure-in | 0.995 | 1.19 |
| kg-bert-bert-for-knowledge-graph-completion | 0.990 | 1.47 |
| translating-embeddings-for-modeling-multi | 0.989 | 1.84 |
| lp-bert-multi-task-pre-training-knowledge | 1.000 | 1.18 |