Research Article
An Approach Based on Multilevel Convolution for Sentence-Level Element Extraction of Legal Text
Table 8
The comparison results on legal dataset of the input embedding of each levels in MCNN.
| | Model | Divorce | Loan | Labor | | HL (-) | Micro-P (+) | Micro-R (+) | Micro-F1 (+) | HL (-) | Micro-P (+) | Micro-R (+) | Micro-F1 (+) | HL (-) | Micro-P (+) | Micro-R (+) | Micro-F1 (+) |
| | TSI | 0.02191 | 0.8799 | 0.8519 | 0.8657 | 0.02826 | 0.8569 | 0.8443 | 0.8506 | 0.01719 | 0.8710 | 0.8507 | 0.8607 | | Our model | 0.02126 | 0.8852 | 0.8728 | 0.8790 | 0.02772 | 0.8633 | 0.8573 | 0.8603 | 0.01688 | 0.8812 | 0.8589 | 0.8699 |
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