Paper: Using String-Kernels For Learning Semantic Parsers

ACL ID P06-1115
Title Using String-Kernels For Learning Semantic Parsers
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

We present a new approach for mapping natural language sentences to their for- mal meaning representations using string- kernel-basedclassifiers. Oursystemlearns theseclassifiersforeveryproductioninthe formallanguagegrammar. Meaningrepre- sentations for novel natural language sen- tences are obtained by finding the most probable semantic parse using these string classifiers. Our experiments on two real- world data sets show that this approach compares favorably to other existing sys- tems and is particularly robust to noise.