Bridging the Word Disambiguation Gap with the Help of OWL and Semantic Web Ontologies

Due to the complexity of natural language, sufficiently reliable Word Sense Disambiguation (WSD) systems are yet to see the daylight in spite of years of work directed towards that goal in Artificial Intelligence, Computational Linguistics and other related disciplines. We describe how the goal could be approached by applying hybrid methods to information sources and knowledge types. The overall aim is to chart the shorfalls of the present WSD systems related to the use of knowledge types and information sources in them. Real world ontologies and other ontologies in the Semantic Web will make a useful contribution towards the WSD knowledge base envisaged here. The inference capabilities inherent in Ontology Web Language (OWL) especially will have an important role to play in natural language disambiguation and knowledge acquisition. The emphasis is on ontologies as one of the important information sources for hybrid WSD.