Relation Extraction On Ace 2005
Métriques
Cross Sentence
Relation classification F1
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Cross Sentence | Relation classification F1 |
|---|---|---|
| dual-pointer-network-for-fast-extraction-of | No | 80.8 |
| entity-relation-extraction-as-multi-turn | No | - |
| combining-neural-networks-and-log-linear | No | 67.7 |
| end-to-end-relation-extraction-using-lstms-on | No | - |
| named-entity-recognition-and-relation | No | - |
| asking-effective-and-diverse-questions-a | No | - |
| a-multi-gate-encoder-for-joint-entity-and | No | - |
| hyspa-hybrid-span-generation-for-scalable | No | - |
| autoregressive-structured-prediction-with | Yes | - |
| a-walk-based-model-on-entity-graphs-for | No | 64.2 |
| entity-relation-and-event-extraction-with | Yes | - |
| two-are-better-than-one-joint-entity-and | No | - |
| pack-together-entity-and-relation-extraction | Yes | - |
| relation-extraction-perspective-from | No | 61.3 |
| relation-extraction-among-multiple-entities | No | 80.5 |
| gollie-annotation-guidelines-improve-zero | - | - |
| extracting-entities-and-relations-with-joint | No | - |
| incremental-joint-extraction-of-entity | No | - |
| span-level-model-for-relation-extraction | No | - |
| a-hierarchical-multi-task-approach-for | No | - |
| end-to-end-neural-relation-extraction-with | No | - |
| a-trigger-sense-memory-flow-framework-for | Yes | - |
| joint-type-inference-on-entities-and | No | - |
| improved-relation-extraction-with-feature | No | 58.2 |
| a-partition-filter-network-for-joint-entity | No | - |
| a-general-framework-for-information | Yes | - |
| a-frustratingly-easy-approach-for-joint | Yes | - |
| hyspa-hybrid-span-generation-for-scalable | - | - |
| iter-iterative-transformer-based-entity | Yes | - |
| going-out-on-a-limb-joint-extraction-of | No | - |