Research map / Architectures and efficiency / RNNs and normalization
Discontinuous Constituent Parsing with Pointer Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the joint Pointer Network and biaffine labeler | Discontinuous constituent parsing · NEGRA, predicted POS tags | F1: 83.2 -> 85.4 | Helped |
| Use the joint Pointer Network and biaffine labeler | Discontinuous constituent parsing · TIGER, predicted POS tags | F1: 82.7 -> 85.3 | Helped |
| Add gold POS tags instead of using predicted POS tags | This work · NEGRA | F1: 85.4 -> 86.1 | Helped |
| Add gold POS tags instead of using predicted POS tags | This work · TIGER | F1: 85.3 -> 86.3 | Helped |
| Remove POS tag embeddings (ablation) | This work · NEGRA | F1: 85.4 -> 85.7 | No clear effect |
| Remove POS tag embeddings (ablation) | This work · TIGER | F1: 85.3 -> 85.7 | No clear effect |
| Remove POS tag embeddings and pretrained word embeddings (ablation) | This work · NEGRA | F1: 85.4 -> 83.7 | Hurt |
| Remove POS tag embeddings and pretrained word embeddings (ablation) | This work · TIGER | F1: 85.3 -> 84.6 | Hurt |
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