Named Entity Recognition on Chinese Resume (test)
96.66F1 ScoreBaseline + BS
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Baseline + BSBoundary Smoothing=true2022.04 | 96.66 | 96.63 | 96.69 | |
| BaselineBoundary Smoothing=false2022.04 | 96.34 | 95.81 | 96.87 | |
| Ma et al. (2020)2022.04 | 96.11 | 96.08 | 96.13 | |
| Wu et al. (2021)2022.04 | 95.98 | — | — | |
| Li et al. (2020a)2022.04 | 95.86 | — | — | |
| CAN ModelArchitecture=Convolutional Attention Network2019.04 | 94.94 | 95.05 | 94.82 | |
| Baseline + CNNArchitecture=CNN + BiGRU + CRF2019.04 | 94.6 | 94.36 | 94.85 | |
| Zhang and Yang 2018Model type=Lattice model2019.04 | 94.46 | 94.81 | 94.11 | |
| Zhang and Yang (2018)2022.04 | 94.46 | 94.81 | 94.11 | |
| Zhang and Yang 2018Model type=char-based LSTM2019.04 | 94.41 | 94.53 | 94.29 | |
| Zhang and Yang 2018Model type=word-based LSTM2019.04 | 94.24 | 94.07 | 94.42 | |
| BaselineArchitecture=BiGRU + CRF2019.04 | 93.73 | 93.71 | 93.74 |