paper-with-me

Papers

Generalized chart constraints for efficient PCFG and TAG parsing

2018-06-27 · ACL 2018 7 · Stefan Grünewald, Sophie Henning, Alexander Koller

Chart constraints, which specify at which string positions a constituent may begin or end, have been shown to speed up chart parsers for PCFGs. We generalize chart constraints to more expressive grammar formalisms and describe a neural tagger which predicts chart constraints at very high precision. Our constraints accelerate both PCFG and TAG parsing, and combine effectively with other pruning techniques (coarse-to-fine and supertagging) for an overall speedup of two orders of magnitude, while improving accuracy.

📄 PDF Abstract BibTeX arXiv:1806.10654

Code (0)

등록된 구현이 없습니다.

Tasks

TAG

Methods 이 논문이 사용한 방법론

Pruning 설명 없음
SPEED The monocular depth estimation (MDE) is the task of estimating depth from a single frame. This information is an essential knowledge in many computer vision tasks such as scene…

Similar Papers 제목 키워드 기반

Depth-bounding is effective: Improvements and evaluation of unsupervised PCFG induction

2018-09-10 · EMNLP 2018 10 · Lifeng Jin, Finale Doshi-Velez, Timothy Miller, William Schuler 외

There have been several recent attempts to improve the accuracy of grammar induction systems by bounding the recursive complexity of the induction model (Ponvert et al., 2011; Noji and Johnson, 2016; Shain et al., 2016; …

Approximating CKY with Transformers

2023-05-03 · Ghazal Khalighinejad, Ollie Liu, Sam Wiseman

We investigate the ability of transformer models to approximate the CKY algorithm, using them to directly predict a sentence's parse and thus avoid the CKY algorithm's cubic dependence on sentence length. We find that on…

Constituency ParsingInductive BiasSentence

Coarse-To-Fine Parsing for Expressive Grammar Formalisms

2017-09-01 · WS 2017 9 · Christoph Teichmann, Alex Koller, er, Jonas Groschwitz

We generalize coarse-to-fine parsing to grammar formalisms that are more expressive than PCFGs and/or describe languages of trees or graphs. We evaluate our algorithm on PCFG, PTAG, and graph parsing. While we achieve th…

Holographic Neural PCFG for Unsupervised Parsing

2026-07-09 · Ryosuke Yamaki, Daichi Mochihashi, Nobutaka Shimada, Tadahiro Taniguchi arxiv

Unsupervised constituency parsing aims to accurately induce latent tree structures from raw text alone. Recent neural parameterizations of PCFGs achieve strong performance in both supervised and unsupervised parsing, yet…

Constituency Parsing

Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs

2012-12-01 · NeurIPS 2012 12 · Michael Collins, Shay B. Cohen

We describe an approach to speed-up inference with latent variable PCFGs, which have been shown to be highly effective for natural language parsing. Our approach is based on a tensor formulation recently introduced for …

Tensor Decomposition