Word Sense Disambiguation using Optimised Combinations of Knowledge Sources
<|reference_start|>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 performs unrestricted 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. The usefulness of these sources is 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.<|reference_end|>
@article{wilks1998word,
    title={Word Sense Disambiguation using Optimised Combinations of Knowledge
  Sources},
    author={Yorick Wilks and Mark Stevenson},
    journal={arXiv preprint arXiv:cmp-lg/9806014},
    year={1998},
    archivePrefix={arXiv},
    eprint={cmp-lg/9806014},
    primaryClass={cmp-lg cs.CL}
}