Research Article
KoRASA: Pipeline Optimization for Open-Source Korean Natural Language Understanding Framework Based on Deep Learning
Table 7
Performance comparison of intent classification.
| Model | Intent classification | Entity extraction | Train | Test | Train | Test | Acc | F1 | Acc | F1 | Acc | F1 | Acc | F1 |
| Keyword | 0.975 | 0.982 | 0.782 | 0.786 | 0.993 | 0.989 | 0.957 | 0.908 | Fallback | 1.000 | 1.000 | 0.980 | 0.981 | 0.993 | 0.989 | 0.959 | 0.905 | DIET-Base | 1.000 | 1.000 | 0.982 | 0.980 | 0.993 | 0.989 | 0.962 | 0.910 | KoRASA | 1.000 | 1.000 | 0.982 | 0.984 | 0.993 | 0.989 | 0.974 | 0.947 |
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