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 151200 of 204 papers

TitleStatusHype
Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic OraclesCode0
Parsing as Language ModelingCode0
Discontinuous Constituency Parsing with a Stack-Free Transition System and a Dynamic OracleCode0
Gaussian Mixture Latent Vector GrammarsCode0
Generalizing Natural Language Analysis through Span-relation RepresentationsCode0
Span-based discontinuous constituency parsing: a family of exact chart-based algorithms with time complexities from O(n^6) down to O(n^3)Code0
Parsing with Traces: An O(n^4) Algorithm and a Structural RepresentationCode0
Grammar as a Foreign LanguageCode0
Grammar Induction with Neural Language Models: An Unusual ReplicationCode0
YellowFin and the Art of Momentum TuningCode0
Head-Driven Phrase Structure Grammar Parsing on Penn TreebankCode0
Direct Output Connection for a High-Rank Language ModelCode0
To be Continuous, or to be Discrete, Those are Bits of QuestionsCode0
Straight to the Tree: Constituency Parsing with Neural Syntactic DistanceCode0
What Do Recurrent Neural Network Grammars Learn About Syntax?Code0
Improved Latent Tree Induction with Distant Supervision via Span ConstraintsCode0
DepNeCTI: Dependency-based Nested Compound Type Identification for SanskritCode0
Probabilistic Graph-based Dependency Parsing with Convolutional Neural NetworkCode0
PTB Graph Parsing with Tree ApproximationCode0
BERT-Proof Syntactic Structures: Investigating Errors in Discontinuous Constituency ParsingCode0
Improving Sequence-to-Sequence Semantic Parser for Task Oriented DialogCode0
Improving Unsupervised Constituency Parsing via Maximizing Semantic InformationCode0
Recurrent Neural Network GrammarsCode0
Investigating Non-local Features for Neural Constituency ParsingCode0
Automatic Extraction of Clausal Embedding Based on Large-Scale English Text DataCode0
Structural Optimization Ambiguity and Simplicity Bias in Unsupervised Neural Grammar InductionCode0
Structured Tree Alignment for Evaluation of (Speech) Constituency ParsingCode0
Rethinking Self-Attention: Towards Interpretability in Neural ParsingCode0
Assessing the Use of Prosody in Constituency Parsing of Imperfect TranscriptsCode0
An Empirical Study of Building a Strong Baseline for Constituency ParsingCode0
Latent Tree Learning with Ordered Neurons: What Parses Does It Produce?Code0
Dependency Induction Through the Lens of Visual PerceptionCode0
Syntactic Parse FusionCode0
Learning Syntax from Naturally-Occurring BracketingsCode0
Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Auto-EncodersCode0
Rule Augmented Unsupervised Constituency ParsingCode0
Less Grammar, More FeaturesCode0
Scheduled Sampling for Sequence Prediction with Recurrent Neural NetworksCode0
LLM-enhanced Self-training for Cross-domain Constituency ParsingCode0
Unlexicalized Transition-based Discontinuous Constituency ParsingCode0
Cross-Domain Generalization of Neural Constituency ParsersCode0
Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary TasksCode0
Multilingual Chart-based Constituency Parse Extraction from Pre-trained Language ModelsCode0
Tetra-Tagging: Word-Synchronous Parsing with Linear-Time InferenceCode0
Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence GenerationCode0
CPTAM: Constituency Parse Tree Aggregation MethodCode0
Approximating CKY with TransformersCode0
Court Judgement Labeling Using Topic Modeling and Syntactic ParsingCode0
Converting the Point of View of Messages Spoken to Virtual AssistantsCode0
Neural Combinatory Constituency ParsingCode0
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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