Coarse-To-Fine Parsing for Expressive Grammar Formalisms
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 the expected performance gains on PCFGs, coarse-to-fine does not help for PTAG and can even slow down parsing for graphs. We discuss the implications of this finding.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Generic refinement of expressive grammar formalisms with an application to discontinuous constituent parsing
We formulate a generalization of Petrov et al. (2006){'}s split/merge algorithm for interpreted regular tree grammars (Koller and Kuhlmann, 2011), which capture a large class of grammar formalisms. We evaluate its effect…
Generalized chart constraints for efficient PCFG and TAG parsing
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 de…
TAGSPARQA: Skeleton-based Semantic Parsing for Complex Questions over Knowledge Bases
Semantic parsing transforms a natural language question into a formal query over a knowledge base. Many existing methods rely on syntactic parsing like dependencies. However, the accuracy of producing such expressive for…
Semantic ParsingSentenceAlto: Rapid Prototyping for Parsing and Translation
We present Alto, a rapid prototyping tool for new grammar formalisms. Alto implements generic but efficient algorithms for parsing, translation, and training for a range of monolingual and synchronous grammar formalisms.…
Machine TranslationSemantic ParsingTranslationAdvances in Using Grammars with Latent Annotations for Discontinuous Parsing
We present new experiments that transfer techniques from Probabilistic Context-free Grammars with Latent Annotations (PCFG-LA) to two grammar formalisms for discontinuous parsing: linear context-free rewriting systems an…