SOTAVerified

Constituency Parsing

Constituency parsing aims to extract a constituency-based parse tree from a sentence that represents its syntactic structure according to a phrase structure grammar.

Example:

             Sentence (S)
                 |
   +-------------+------------+
   |                          |
 Noun (N)                Verb Phrase (VP)
   |                          |
 John                 +-------+--------+
                      |                |
                    Verb (V)         Noun (N)
                      |                |
                    sees              Bill

Recent approaches convert the parse tree into a sequence following a depth-first traversal in order to be able to apply sequence-to-sequence models to it. The linearized version of the above parse tree looks as follows: (S (N) (VP V N)).

Papers

Showing 125 of 204 papers

TitleStatusHype
Grammar-Constrained Decoding for Structured NLP Tasks without FinetuningCode2
DadmaTools: Natural Language Processing Toolkit for Persian LanguageCode2
Unsupervised Discontinuous Constituency Parsing with Mildly Context-Sensitive GrammarsCode1
On Parsing as TaggingCode1
TreeMix: Compositional Constituency-based Data Augmentation for Natural Language UnderstandingCode1
Challenges to Open-Domain Constituency ParsingCode1
Learned Incremental Representations for ParsingCode1
Nested Named Entity Recognition as Latent Lexicalized Constituency ParsingCode1
Bottom-Up Constituency Parsing and Nested Named Entity Recognition with Pointer NetworksCode1
ELIT: Emory Language and Information ToolkitCode1
Headed-Span-Based Projective Dependency ParsingCode1
N-ary Constituent Tree Parsing with Recursive Semi-Markov ModelCode1
Nested Named Entity Recognition with Partially-Observed TreeCRFsCode1
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language ModelingCode1
Strongly Incremental Constituency Parsing with Graph Neural NetworksCode1
Improving Constituency Parsing with Span AttentionCode1
Fast and Accurate Neural CRF Constituency ParsingCode1
Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive AutoencodersCode1
Multilingual Constituency Parsing with Self-Attention and Pre-TrainingCode1
Constituency Parsing with a Self-Attentive EncoderCode1
Automatic Extraction of Clausal Embedding Based on Large-Scale English Text DataCode0
Revisiting Absence withSymptoms that *T* Show up Decades Later to Recover Empty Categories0
An Attempt to Develop a Neural Parser based on Simplified Head-Driven Phrase Structure Grammar on Vietnamese0
Improving Unsupervised Constituency Parsing via Maximizing Semantic InformationCode0
Entity-Aware Biaffine Attention Model for Improved Constituent Parsing with Reduced Entity Violations0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Hashing + XLNetF1 score96.43Unverified
2SAPar + XLNetF1 score96.4Unverified
3Label Attention Layer + HPSG + XLNetF1 score96.38Unverified
4Attach-Juxtapose Parser + XLNetF1 score96.34Unverified
5Head-Driven Phrase Structure Grammar Parsing (Joint) + XLNetF1 score96.33Unverified
6CRF Parser + RoBERTaF1 score96.32Unverified
7Hashing + BertF1 score96.03Unverified
8NFC + BERT-largeF1 score95.92Unverified
9N-ary semi-markov + BERT-largeF1 score95.92Unverified
10Head-Driven Phrase Structure Grammar Parsing (Joint) + BERTF1 score95.84Unverified
#ModelMetricClaimedVerifiedStatus
1Attach-Juxtapose Parser + BERTF1 score93.52Unverified
2SAPar + BERTF1 score92.66Unverified
3N-ary semi-markov + BERTF1 score92.5Unverified
4Hashing + BertF1 score92.33Unverified
5CRF Parser + BERTF1 score92.27Unverified
6Kitaev etal. 2019F1 score91.75Unverified
7CRF ParserF1 score89.8Unverified
8Zhou etal. 2019F1 score89.4Unverified
9Kitaev etal. 2018F1 score87.43Unverified
#ModelMetricClaimedVerifiedStatus
1CRF Parser + ElectraF1 score91.92Unverified
2CRF Parser + BERTF1 score91.55Unverified
3CRF ParserF1 score88.6Unverified
#ModelMetricClaimedVerifiedStatus
1SAParF183.26Unverified