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 1–50 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 Categories—0
An Attempt to Develop a Neural Parser based on Simplified Head-Driven Phrase Structure Grammar on Vietnamese—0
Improving Unsupervised Constituency Parsing via Maximizing Semantic InformationCode0
Entity-Aware Biaffine Attention Model for Improved Constituent Parsing with Reduced Entity Violations—0
Structural Optimization Ambiguity and Simplicity Bias in Unsupervised Neural Grammar InductionCode0
To be Continuous, or to be Discrete, Those are Bits of QuestionsCode0
jp-evalb: Robust Alignment-based PARSEVAL Measures—0
Unsupervised Parsing by Searching for Frequent Word Sequences among Sentences with Equivalent Predicate-Argument Structures—0
Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages—0
Tree-Averaging Algorithms for Ensemble-Based Unsupervised Discontinuous Constituency ParsingCode0
Structured Tree Alignment for Evaluation of (Speech) Constituency ParsingCode0
Sketch-Guided Constrained Decoding for Boosting Blackbox Large Language Models without Logit AccessCode0
Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence GenerationCode0
LLM-enhanced Self-training for Cross-domain Constituency ParsingCode0
Constituency Parsing using LLMs—0
Simple Hardware-Efficient PCFGs with Independent Left and Right Productions—0
DepNeCTI: Dependency-based Nested Compound Type Identification for SanskritCode0
Ensemble Distillation for Unsupervised Constituency ParsingCode0
DiffCloth: Diffusion Based Garment Synthesis and Manipulation via Structural Cross-modal Semantic Alignment—0
Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approach—0
Approximating CKY with TransformersCode0
Cascading and Direct Approaches to Unsupervised Constituency Parsing on Spoken SentencesCode0
Do Transformers Parse while Predicting the Masked Word?—0
Re-evaluating the Need for Multimodal Signals in Unsupervised Grammar Induction—0
Fast Rule-Based Decoding: Revisiting Syntactic Rules in Neural Constituency Parsing—0
Joint Chinese Word Segmentation and Span-based Constituency Parsing—0
Order-sensitive Neural Constituency Parsing—0
Shift-Reduce Task-Oriented Semantic Parsing with Stack-TransformersCode0
Improving Low-resource RRG Parsing with Cross-lingual Self-training—0
Show:102550
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Benchmark Results

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