  This paper presents a corpus-based approach to word sense disambiguation
where a decision tree assigns a sense to an ambiguous word based on the bigrams
that occur nearby. This approach is evaluated using the sense-tagged corpora
from the 1998 SENSEVAL word sense disambiguation exercise. It is more accurate
than the average results reported for 30 of 36 words, and is more accurate than
the best results for 19 of 36 words.
