Abstract
In this paper, we propose a new method for verb sense disambiguation.Word sensedisambiguation (WSD) has been recognized as one of the most important subjects innatural language processing, and there has been several reports on the subject. Mostof previous works can be classified into two approaches from the viewpoint of thetreatment of context including target word;an approach using some words around atarget word (n-word window) and one using syntactic relations (selectional restriction). However, each treatment in these two approaches is different from each other, consequently there is a limitation in an accuracy. We can make the statement thatour method has the merits on both previous approaches, because our method usesthe whole dependency structure of a sentence. We find a similarity between contextsbased on a pairwise alignment technique which is used generally to measure a similarityon DNA sequences. Using our method, we can achieve WSD in more flexiblyand robustly than the methods proposed previously. In our experiment, we obtainedan accuracy of 81.1% on average by the new method with supervised learning byhand.
