Browse State-of-the-Art › Dependency Parsing

Dependency Parsing

338 papers with code · 16 benchmarks · 15 datasets archive 2025-07-28

Natural Language Processing

Dependency parsing is the task of extracting a dependency parse of a sentence that represents its grammatical structure and defines the relationships between "head" words and words, which modify those heads.

Example:

     root
      |
      | +-------dobj---------+
      | |                    |
nsubj | |   +------det-----+ | +-----nmod------+
+--+  | |   |              | | |               |
|  |  | |   |      +-nmod-+| | |      +-case-+ |
+  |  + |   +      +      || + |      +      | |
I  prefer  the  morning   flight  through  Denver

Relations among the words are illustrated above the sentence with directed, labeled arcs from heads to dependents (+ indicates the dependent).

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

16 leaderboard tables shown for this task, 16 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted. 10 shown of 16 until expanded.

DatasetBest model (first row in archive order)PaperCodeSyntologyCompare
Penn Treebank (22 rows) Label Attention Layer + HPSG + XLNet Rethinking Self-Attention: Towards Interpretability in Neural Parsing code Syntology ran 1 of 3 samples · 2 unverified Compare
Universal Dependencies (6 rows) UDPipe 2.0 + mBERT + FLAIR Evaluating Contextualized Embeddings on 54 Languages in POS... — — Compare
GENIA - LAS (3 rows) BiLSTM-CRF From POS tagging to dependency parsing for biomedical event extraction code — Compare
GENIA - UAS (3 rows) BiLSTM-CRF From POS tagging to dependency parsing for biomedical event extraction code — Compare
Tweebank (3 rows) SuPar-BERTweet Cross-Dialect Social Media Dependency Parsing for Social... code — Compare
CoNLL-2009 (2 rows) CRFPar Efficient Second-Order TreeCRF for Neural Dependency Parsing code Syntology ran 2 of 3 samples · 1 unverified Compare
French GSD (2 rows) CamemBERT CamemBERT: a Tasty French Language Model code — Compare
ParTUT (2 rows) CamemBERT CamemBERT: a Tasty French Language Model code — Compare
Sequoia Treebank (2 rows) CamemBERT CamemBERT: a Tasty French Language Model code — Compare
Spoken Corpus (2 rows) CamemBERT CamemBERT: a Tasty French Language Model code — Compare
UD2.5 test (2 rows) Trankit Trankit: A Light-Weight Transformer-based Toolkit for Multilingual... code — Compare
100STLYE-Labelled (1 row) nlp The CMU METAL Farsi NLP Approach code — Compare
Chinese Treebank (1 row) MFVI Second-Order Neural Dependency Parsing with Message Passing and... code — Compare
DaNE (1 row) da_dacy_large_tft DaCy: A Unified Framework for Danish NLP — — Compare
NLPCC-2019 (1 row) CRFPar Efficient Second-Order TreeCRF for Neural Dependency Parsing code Syntology ran 2 of 3 samples · 1 unverified Compare
Universal Dependency Treebank (1 row) Stanza Stanza: A Python Natural Language Processing Toolkit for Many... code Syntology ran 16 of 30 samples · 14 unverified Compare

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

15 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

5 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 338 papers with code (1,407 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.

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