Year: 2006
Type: conference-paper
Abstract: We present a new approach for mapping natural language sentences to their formal meaning representations using string-kernel-based classifiers. Our system learns these classifiers for every production in the formal language grammar. Meaning representations for novel natural language sentences 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 systems and is particularly robust to noise.
Authors: Rohit J. Kate, Raymond J. Mooney
Institution: The University of Texas at Austin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2140266767