Title :
Searching Semantic Resources for Complex Selectional Restictions to Support Lexical Acquisition
Author :
Taylor, Merwyn ; Carlson, Lynn ; Fontaine, Sun ; Poisson, Stephanie
Author_Institution :
MITRE Corp., McLean, VA, USA
Abstract :
Natural language processing systems are increasingly using ontologies and other large-scale semantic resources to support Verb Sense Disambiguation (VSD) and other applications. One of the ways in which these resources can be used is to identify the selectional restrictions on verb arguments needed for sense distinction. However, manually navigating such resources can be difficult and inefficient due to their size and complexity. In this paper, we present a process for automatically searching through an ontology to determine appropriate concepts for expressing selectional restrictions on verb sense. The goal of this research is to semi-automate the development of a semantically rich lexicon to support high-precision information extraction.
Keywords :
computational linguistics; information retrieval; learning (artificial intelligence); natural language processing; ontologies (artificial intelligence); complex selectional restrictions; high-precision information extraction; large-scale semantic resource searching; lexical acquisition support; natural language processing systems; ontologies; semantically rich lexicon; supervised learning; verb arguments; verb sense disambiguation; Data mining; Large-scale systems; Length measurement; Natural language processing; Navigation; Ontologies; Robustness; Sun; Supervised learning; Taxonomy; concept search; selectional restrictions; supervised learning;
Conference_Titel :
Advances in Semantic Processing, 2009. SEMAPRO '09. Third International Conference on
Conference_Location :
Sliema
Print_ISBN :
978-1-4244-5044-2
Electronic_ISBN :
978-0-7695-3833-4
DOI :
10.1109/SEMAPRO.2009.14
