Paper: Semantic Kernels for Semantic Parsing

ACL ID D14-1050
Title Semantic Kernels for Semantic Parsing
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014

We present an empirical study on the use of semantic information for Concept Seg- mentation and Labeling (CSL), which is an important step for semantic parsing. We represent the alternative analyses out- put by a state-of-the-art CSL parser with tree structures, which we rerank with a classifier trained on two types of seman- tic tree kernels: one processing structures built with words, concepts and Brown clusters, and another one using semantic similarity among the words composing the structure. The results on a corpus from the restaurant domain show that our semantic kernels exploiting similarity measures out- perform state-of-the-art rerankers.