Supervised Disambiguation Bayesian classification (Gale et al, 1992): look at the words around an ambiguous word in a large context window. Each content word contributes potentially useful information about which sense of the ambiguous word is likely to be used with it. The classifier does no feature selection; it simply combines the evidence from all features, assuming they are independent Bayes decision rule: Decide s if P(S1>PGld for Sk t Optimal because it minimizes the probability of error; for each individual case it selects the class with the highest conditional probability(and hence owest error rate) a Error rate for a sequence will also be minimized 20212/5 Natural Language Processing--Word Sense Disambiguation 72021/2/5 Natural Language Processing -- Word Sense Disambiguation 7 Supervised Disambiguation: Bayesian Classification ◼ (Gale et al, 1992): look at the words around an ambiguous word in a large context window. Each content word contributes potentially useful information about which sense of the ambiguous word is likely to be used with it. The classifier does no feature selection; it simply combines the evidence from all features, assuming they are independent. ◼ Bayes decision rule: Decide s ’ if P(s ’|c) > P(sk|c) for sk ≠s ’ ◼ Optimal because it minimizes the probability of error; for each individual case it selects the class with the highest conditional probability (and hence lowest error rate). ◼ Error rate for a sequence will also be minimized