Online Structured Learning for Semantic Parsing with Synchronous and lambda-Synchronous Context Free Grammars

We formulate semantic parsing as a parsing problem on a synchronous context free grammar (SCFG) which is automatically built on the corpus of natural language sentences and the representation of semantic outputs. We then present an online learning framework for estimating the synchronous SCFG grammar. In addition, our online learning methods for semantic parsing problems are also extended to deal with the case, in which the semantic representation could be represented under lambda-calculus. Experimental results in the domain of semantic parsing show advantages in comparison with previous works.