Named Entity Recognition On Ace 2004
Métriques
F1
Multi-Task Supervision
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | F1 | Multi-Task Supervision | Paper Title | Repository |
|---|---|---|---|---|
| Neural transition-based model | 73.3 | n | A Neural Transition-based Model for Nested Mention Recognition | |
| Ours: cross-sentence ALB | 90.3 | y | A Frustratingly Easy Approach for Entity and Relation Extraction | |
| Neural segmental hypergraphs | 75.1 | n | Neural Segmental Hypergraphs for Overlapping Mention Recognition | |
| BoningKnife | 86.41 | n | BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge | - |
| PIQN | 88.14 | n | Parallel Instance Query Network for Named Entity Recognition | |
| seq2seq+BERT+Flair | 84.40 | n | Neural Architectures for Nested NER through Linearization | |
| MGNER | 79.5 | n | Multi-Grained Named Entity Recognition | |
| Second-best learning and decoding | 85.82 | n | Nested Named Entity Recognition via Second-best Sequence Learning and Decoding | |
| Biaffine-NER | 86.7 | n | Named Entity Recognition as Dependency Parsing |
0 of 9 row(s) selected.