Paper: A Statistical Semantic Parser That Integrates Syntax And Semantics

ACL ID W05-0602
Title A Statistical Semantic Parser That Integrates Syntax And Semantics
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005
Authors

We introduce a learning semantic parser, SCISSOR, that maps natural-language sen- tences to a detailed, formal, meaning- representation language. It first uses an integrated statistical parser to pro- duce a semantically augmented parse tree, in which each non-terminal node has both a syntactic and a semantic label. A compositional-semantics procedure is then used to map the augmented parse tree into a final meaning representation. We evaluate the system in two domains, a natural-language database interface and an interpreter for coaching instructions in robotic soccer. We present experimental results demonstrating that SCISSOR pro- duces more accurate semantic representa- tions than several previous approaches.