Complex Query Answering On Fb15K
Métriques
MRR 1p
MRR 2i
MRR 2p
MRR 2u
MRR 3i
MRR 3p
MRR ip
MRR pi
MRR up
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | MRR 1p | MRR 2i | MRR 2p | MRR 2u | MRR 3i | MRR 3p | MRR ip | MRR pi | MRR up |
|---|---|---|---|---|---|---|---|---|---|
| answering-complex-logical-queries-on | 0.895 | 0.803 | 0.674 | 0.767 | 0.836 | 0.588 | 0.740 | 0.752 | 0.613 |
| complex-query-answering-with-neural-link-1 | - | - | - | - | - | - | - | - | - |
| neural-symbolic-models-for-logical-queries-on | 0.885 | 0.797 | 0.693 | 0.741 | 0.835 | 0.587 | 0.704 | 0.699 | 0.610 |
| adapting-neural-link-predictors-for-complex | 0.892 | 0.761 | 0.645 | 0.684 | 0.794 | 0.579 | 0.706 | 0.701 | 0.579 |
| embedding-logical-queries-on-knowledge-graphs | 0.546 | 0.397 | 0.153 | 0.221 | 0.514 | 0.108 | 0.191 | 0.276 | 0.116 |
| query2box-reasoning-over-knowledge-graphs-in-1 | 0.68 | 0.551 | 0.21 | 0.351 | 0.665 | 0.142 | 0.261 | 0.394 | 0.167 |
| complex-query-answering-with-neural-link-1 | 0.892 | 0.771 | 0.653 | 0.723 | 0.806 | - | 0.716 | - | - |
| complex-query-answering-with-neural-link-1 | - | - | - | - | - | - | - | - | - |
| beta-embeddings-for-multi-hop-logical | 0.651 | 0.558 | 0.257 | 0.401 | 0.665 | 0.247 | 0.281 | 0.439 | 0.252 |