Nested Mention Recognition On Ace 2004
Metrics
F1
Results
Performance results of various models on this benchmark
Model Name | F1 | Paper Title | Repository |
|---|---|---|---|
| MGNER | 79.5 | Multi-Grained Named Entity Recognition | - |
| seq2seq+BERT+Flair | 84.40 | Neural Architectures for Nested NER through Linearization | - |
| Neural segmental hypergraphs | 75.1 | Neural Segmental Hypergraphs for Overlapping Mention Recognition | - |
| BERT-MRC | 85.98 | A Unified MRC Framework for Named Entity Recognition | - |
| Second-best learning and decoding | 85.82 | Nested Named Entity Recognition via Second-best Sequence Learning and Decoding | - |
| Neural transition-based model | 73.1 | A Neural Transition-based Model for Nested Mention Recognition | - |
| BoningKnife | 86.41 | BoningKnife: Joint Entity Mention Detection and Typing for Nested NER via prior Boundary Knowledge | - |
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