Word Sense Disambiguation using Optimised Combinations of Knowledge Sources

Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. We describe a system which t)erforms word sense disambiguation on all content words in free text by combining different knowledge sources: semantic preferences, dictionary definitions and subject/domain codes along with part-of-speech tags, optimised by means of a learning algorithm. We also describe the creation of a new sense tagged corpus by combining existing resources. Tested accuracy of our approach on this corpus exceeds 92%, demonstrating the viability of all-word disambiguation rather than restricting oneself to a small sample.

• Type: Conference
• Year: 1998
• Where: ACL
• Authors: Yorick Wilks, Mark Stevenson
• Keywords: ACL 1998, ACL 2007, Knowledge Sources, Sense Disambiguation Algorithms, Word Sense Disambiguation