Chinese Named Entity Recognition On Resume
评估指标
F1
评测结果
各个模型在此基准测试上的表现结果
比较表格
| 模型名称 | F1 |
|---|---|
| boundary-smoothing-for-named-entity-1 | 96.66 |
| chinese-ner-using-lattice-lstm | 94.46 |
| improving-named-entity-recognition-with | 96.62 |
| flat-chinese-ner-using-flat-lattice | 95.45 |
| glyce-glyph-vectors-for-chinese-character | 96.54 |
| flat-chinese-ner-using-flat-lattice | 95.86 |
| fgn-fusion-glyph-network-for-chinese-named | 96.79 |
| tener-adapting-transformer-encoder-for-name | 95 |
| simplify-the-usage-of-lexicon-in-chinese-ner | 95.59 |
| slk-ner-exploiting-second-order-lexicon | 95.8 |
| improving-named-entity-recognition-by | 96.87 |
| nflat-non-flat-lattice-transformer-for | 95.58 |
| can-ner-convolutional-attention-network | 94.94 |