In practical applications, decoding speed is very important. Modern structured learning technique adopts template based method to extract millions of features. Complicated templat...
We propose a non-parametric Bayesian model for unsupervised semantic parsing. Following Poon and Domingos (2009), we consider a semantic parsing setting where the goal is to (1) d...
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
We describe a bidirectional framework for natural language parsing and generation, using a typedfeatureformalismand an HPSG-based grammar with a parser and generator derived from ...
Counts from large corpora (like the web) can be powerful syntactic cues. Past work has used web counts to help resolve isolated ambiguities, such as binary noun-verb PP attachment...