Hierarchical A (HA) uses of a hierarchy of coarse grammars to speed up parsing without sacrificing optimality. HA prioritizes search in refined grammars using Viterbi outside cost...
This paper studies two methods for training hierarchical MT rules independently of word alignments. Bilingual chart parsing and EM algorithm are used to train bitext correspondenc...
We consider the problem of learning factored probabilistic CCG grammars for semantic parsing from data containing sentences paired with logical-form meaning representations. Tradi...
Tom Kwiatkowski, Luke S. Zettlemoyer, Sharon Goldw...
We investigate a number of approaches to generating Stanford Dependencies, a widely used semantically-oriented dependency representation. We examine algorithms specifically design...
Daniel Cer, Marie-Catherine de Marneffe, Daniel Ju...
Abstract. The purpose of this paper is (1) to provide a theoretical justification for the use of Monte-Carlo sampling for approximate resolution of NP-hard maximization problems in...