Table 7 Comparison of experimental results of five kinds of entities recognition of our method and the segment-level neural network
From: Named entity recognition for Chinese judgment documents based on BiLSTM and CRF
| Methods | Entity type | Precision | Recall | F1 |
|---|---|---|---|---|
| Our method | Person name | 77.08 | 73.69 | 75.35 |
| Organization name | 66.69 | 61.48 | 64.10 | |
| Laws and regulation | 92.59 | 94.34 | 93.46 | |
| Accusation | 76.67 | 71.43 | 73.95 | |
| Penalty | 77.12 | 72.80 | 74.90 | |
| Overall | 77.08 | 73.69 | 75.35 | |
| Segment-level neural network | Person name | 80.54 | 84.08 | 82.27 |
| Organization name | 62.55 | 69.68 | 65.92 | |
| Laws and regulation | 15.54 | 26.14 | 19.49 | |
| Accusation | 82.12 | 75.12 | 78.47 | |
| Penalty | 35.96 | 47.29 | 40.85 | |
| Overall | 71.60 | 69.40 | 70.48 |