Best Paper Award
In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007), pp. 960-967, Prague, Czech Republic, June 2007.
Paper ID: 199
Category: Natural Language Learning, Learning for Semantic Parsing, Advice-Taking Learners
This paper presents the first empirical results to our knowledge on learning synchronous grammars that generate logical forms. Using statistical machine translation techniques, a semantic parser based on a synchronous context-free grammar augmented with lambda-operators is learned given a set of training sentences and their correct logical forms. The resulting parser is shown to be the best-performing system so far in a database query domain.
