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 131–140 of 204 papers

Title	Date	Tasks	Status
A Generative Parser with a Discriminative Recognition Algorithm	Aug 1, 2017	Constituency ParsingDecoder	—Unverified
A Minimal Span-Based Neural Constituency Parser	May 10, 2017	Constituency Parsing	—Unverified
A Multi-Teraflop Constituency Parser using GPUs	Oct 1, 2013	Constituency Parsing	—Unverified
An Attempt to Develop a Neural Parser based on Simplified Head-Driven Phrase Structure Grammar on Vietnamese	Nov 26, 2024	ARCConstituency Parsing	—Unverified
An Empirical Comparison of Unsupervised Constituency Parsing Methods	Jul 1, 2020	Constituency Parsing	—Unverified
An Empirical Investigation of Error Types in Vietnamese Parsing	Aug 1, 2018	Constituency ParsingPart-Of-Speech Tagging	—Unverified
An Empirical Investigation of Statistical Significance in NLP	Jul 1, 2012	Constituency ParsingMachine Translation	—Unverified
An Empirical Study for Vietnamese Constituency Parsing with Pre-training	Oct 19, 2020	Constituency ParsingDecoder	—Unverified
A New Version of the Sk Treebank of Polish Harmonised with the Walenty Valency Dictionary	May 1, 2018	Constituency Parsing	—Unverified
Assigning Deep Lexical Types Using Structured Classifier Features for Grammatical Dependencies	Jul 1, 2012	Constituency ParsingLanguage Modelling	—Unverified

Show:10 25 50

← PrevPage 14 of 21Next →

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