Papers › Simpler but More Accurate Semantic Dependency Parsing
Simpler but More Accurate Semantic Dependency Parsing
Timothy Dozat, Christopher D. Manning
While syntactic dependency annotations concentrate on the surface or functional structure of a sentence, semantic dependency annotations aim to capture between-word relationships that are more closely related to the meaning of a sentence, using graph-structured representations. We extend the LSTM-based syntactic parser of Dozat and Manning (2017) to train on and generate these graph structures. The resulting system on its own achieves state-of-the-art performance, beating the previous, substantially more complex state-of-the-art system by 0.6% labeled F1. Adding linguistically richer input representations pushes the margin even higher, allowing us to beat it by 1.9% labeled F1.
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a5c80be490bf38e6 · report
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Semantic Dependency Parsing | DM | Dozat et al. (2018) | In-domain | 93.7 | #4 of 4 | Archive leaderboard | report |
| Semantic Dependency Parsing | DM | Dozat et al. (2018) | Out-of-domain | 88.9 | #4 of 4 | Archive leaderboard | report |
| Semantic Dependency Parsing | PAS | Dozat et al. (2018) | In-domain | 93.9 | #4 of 4 | Archive leaderboard | report |
| Semantic Dependency Parsing | PAS | Dozat et al. (2018) | Out-of-domain | 90.6 | #4 of 4 | Archive leaderboard | report |
| Semantic Dependency Parsing | PSD | Dozat et al. (2018) | In-domain | 81.0 | #4 of 4 | Archive leaderboard | report |
| Semantic Dependency Parsing | PSD | Dozat et al. (2018) | Out-of-domain | 79.4 | #4 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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