Complex Query Answering On Fb15K
평가 지표
MRR 1p
MRR 2i
MRR 2p
MRR 2u
MRR 3i
MRR 3p
MRR ip
MRR pi
MRR up
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | 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 |