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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 91–100 of 204 papers

Title	Date	Tasks	Status
An Empirical Comparison of Unsupervised Constituency Parsing Methods	Jul 1, 2020	Constituency Parsing	—Unverified
Efficient Constituency Parsing by Pointing	Jun 24, 2020	Constituency Parsing	—Unverified
Qu'apporte BERT \`a l'analyse syntaxique en constituants discontinus ? Une suite de tests pour \'evaluer les pr\'edictions de structures syntaxiques discontinues en anglais (What does BERT contribute to discontinuous constituency parsing ? A test suite to evaluate discontinuous constituency structure predictions in English)	Jun 1, 2020	Constituency Parsing	—Unverified
Multilingual Chart-based Constituency Parse Extraction from Pre-trained Language Models	Apr 8, 2020	Constituency ParsingCross-Lingual Transfer	CodeCode Available
At Which Level Should We Extract? An Empirical Analysis on Extractive Document Summarization	Apr 6, 2020	Constituency ParsingDocument Summarization	—Unverified
Span-based discontinuous constituency parsing: a family of exact chart-based algorithms with time complexities from O(n^6) down to O(n^3)	Mar 30, 2020	Constituency ParsingWord Embeddings	CodeCode Available
Learning Syntactic and Dynamic Selective Encoding for Document Summarization	Mar 25, 2020	Constituency ParsingDecoder	—Unverified
Unsupervised Discourse Constituency Parsing Using Viterbi EM	Jan 1, 2020	Constituency ParsingDiscourse Parsing	CodeCode Available
Rethinking Self-Attention: Towards Interpretability in Neural Parsing	Nov 10, 2019	Constituency ParsingDependency Parsing	CodeCode Available
Generalizing Natural Language Analysis through Span-relation Representations	Nov 10, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available

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All datasets Penn Treebank CTB5 CTB7 ATB

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Hashing + XLNet	F1 score	96.43	—	Unverified
2	SAPar + XLNet	F1 score	96.4	—	Unverified
3	Label Attention Layer + HPSG + XLNet	F1 score	96.38	—	Unverified
4	Attach-Juxtapose Parser + XLNet	F1 score	96.34	—	Unverified
5	Head-Driven Phrase Structure Grammar Parsing (Joint) + XLNet	F1 score	96.33	—	Unverified
6	CRF Parser + RoBERTa	F1 score	96.32	—	Unverified
7	Hashing + Bert	F1 score	96.03	—	Unverified
8	N-ary semi-markov + BERT-large	F1 score	95.92	—	Unverified
9	NFC + BERT-large	F1 score	95.92	—	Unverified
10	Head-Driven Phrase Structure Grammar Parsing (Joint) + BERT	F1 score	95.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Attach-Juxtapose Parser + BERT	F1 score	93.52	—	Unverified
2	SAPar + BERT	F1 score	92.66	—	Unverified
3	N-ary semi-markov + BERT	F1 score	92.5	—	Unverified
4	Hashing + Bert	F1 score	92.33	—	Unverified
5	CRF Parser + BERT	F1 score	92.27	—	Unverified
6	Kitaev etal. 2019	F1 score	91.75	—	Unverified
7	CRF Parser	F1 score	89.8	—	Unverified
8	Zhou etal. 2019	F1 score	89.4	—	Unverified
9	Kitaev etal. 2018	F1 score	87.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CRF Parser + Electra	F1 score	91.92	—	Unverified
2	CRF Parser + BERT	F1 score	91.55	—	Unverified
3	CRF Parser	F1 score	88.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SAPar	F1	83.26	—	Unverified