Ucca Parsing On Conll 2019
평가 지표
Full MRP F1
Full UCCA F1
LPP MRP F1
LPP UCCA F1
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | Full MRP F1 | Full UCCA F1 | LPP MRP F1 | LPP UCCA F1 | Paper Title | Repository |
|---|---|---|---|---|---|---|
| Transition-based (+BERT + Efficient Training + Effective Encoding) | 81.7 | 66.7 | 82.6 | 64.4 | HIT-SCIR at MRP 2019: A Unified Pipeline for Meaning Representation Parsing via Efficient Training and Effective Encoding | - |
| Transition-based (+BERT + MTL) | 64.1 | 35.6 | 73.1 | 50.3 | TUPA at MRP 2019: A Multi-Task Baseline System | - |
| Transition-based (+BERT) | 77.7 | 57.4 | 82.2 | 65.9 | TUPA at MRP 2019: A Multi-Task Baseline System | - |
0 of 3 row(s) selected.