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Constituency Parsing

30 papers with code · Natural Language Processing

Consituency 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)).

Benchmarks

Greatest papers with code

Attention Is All You Need

NeurIPS 2017 tensorflow/models

The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration.

CONSTITUENCY PARSING MACHINE TRANSLATION

Grammar as a Foreign Language

NeurIPS 2015 atpaino/deep-text-corrector

Syntactic constituency parsing is a fundamental problem in natural language processing and has been the subject of intensive research and engineering for decades.

CONSTITUENCY PARSING

Multilingual Constituency Parsing with Self-Attention and Pre-Training

ACL 2019 nikitakit/self-attentive-parser

We show that constituency parsing benefits from unsupervised pre-training across a variety of languages and a range of pre-training conditions.

CONSTITUENCY PARSING

Constituency Parsing with a Self-Attentive Encoder

ACL 2018 nikitakit/self-attentive-parser

We demonstrate that replacing an LSTM encoder with a self-attentive architecture can lead to improvements to a state-of-the-art discriminative constituency parser.

CONSTITUENCY PARSING

YellowFin and the Art of Momentum Tuning

ICLR 2018 JianGoForIt/YellowFin

We revisit the momentum SGD algorithm and show that hand-tuning a single learning rate and momentum makes it competitive with Adam.

CONSTITUENCY PARSING LANGUAGE MODELLING

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

NeurIPS 2015 theamrzaki/text_summurization_abstractive_methods

Recurrent Neural Networks can be trained to produce sequences of tokens given some input, as exemplified by recent results in machine translation and image captioning.

CONSTITUENCY PARSING CURRICULUM LEARNING IMAGE CAPTIONING SPEECH RECOGNITION

Effective Self-Training for Parsing

NAACL 2006 BLLIP/bllip-parser

We present a simple, but surprisingly effective, method of self-training a two-phase parser-reranker system using readily available unlabeled data.

Ranked #14 on Constituency Parsing on Penn Treebank (using extra training data)

CONSTITUENCY PARSING

Fast and Accurate Neural CRF Constituency Parsing

IJCAI 2020 yzhangcs/parser

Estimating probability distribution is one of the core issues in the NLP field.

CONSTITUENCY PARSING DEPENDENCY PARSING