A Reexamination of MRD-based Word Sense Disambiguation
This paper reconsiders the task of MRD-based word sense disambiguation, in extending the basic Lesk algorithm to investigate the impact on WSD performance of different tokenisation schemes and methods of definition extension. In experimentation over the Hinoki Sensebank and the Japanese Senseval-2 dictionary task, we demonstrate that sense-sensitive definition extension over hyponyms, hypernyms and synonyms, combined with definition extension and word tokenisation leads to WSD accuracy above both unsupervised and supervised baselines. In doing so, we demon- strate the utility of ontology induction and establish new opportunities for the development of baseline unsupervised WSD methods.
Keywords: Text Analysis; Language Parsing and Understanding