Papers › Deep Biaffine Attention for Neural Dependency Parsing
Deep Biaffine Attention for Neural Dependency Parsing
Timothy Dozat, Christopher D. Manning
This paper builds off recent work from Kiperwasser & Goldberg (2016) using neural attention in a simple graph-based dependency parser. We use a larger but more thoroughly regularized parser than other recent BiLSTM-based approaches, with biaffine classifiers to predict arcs and labels. Our parser gets state of the art or near state of the art performance on standard treebanks for six different languages, achieving 95.7% UAS and 94.1% LAS on the most popular English PTB dataset. This makes it the highest-performing graph-based parser on this benchmark---outperforming Kiperwasser Goldberg (2016) by 1.8% and 2.2%---and comparable to the highest performing transition-based parser (Kuncoro et al., 2016), which achieves 95.8% UAS and 94.6% LAS. We also show which hyperparameter choices had a significant effect on parsing accuracy, allowing us to achieve large gains over other graph-based approaches.
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Code
Syntology Ran 3 of 19 code samples harvested from 6 repositories linked to this paper; 16 have no recorded run. Of those that ran: 1 ran · violated contract; 1 ran · our draft was wrong; 1 ran · fixture could not drive it.
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Dependency Parsing | CoNLL-2009 | Biaffine Parser | LAS | 85.38 | #2 of 2 | Archive leaderboard | report |
| Dependency Parsing | CoNLL-2009 | Biaffine Parser | UAS | 88.90 | #2 of 2 | Archive leaderboard | report |
| Dependency Parsing | Penn Treebank | Deep Biaffine + RoBERTa | LAS | 95.75 | #4 of 22 | Archive leaderboard | report |
| Dependency Parsing | Penn Treebank | Deep Biaffine + RoBERTa | UAS | 97.29 | #4 of 22 | Archive leaderboard | report |
| Dependency Parsing | Penn Treebank | Deep Biaffine | LAS | 94.22 | #13 of 22 | Archive leaderboard | report |
| Dependency Parsing | Penn Treebank | Deep Biaffine | UAS | 95.87 | #13 of 22 | 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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