We report on experiments in reference resolution using a decision tree approach. We started with a standard feature set used in previous work, which led to moderate results. A closer examination of the performance of the features for different forms of anaphoric expressions showed good results for pronouns, moderate results for proper names, and poor results for definite noun phrases. We then included a cheap, language and domain independent feature based on the minimum edit distance between

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... distance between strings. This feature yielded a significant improvement for data sets consisting of definite noun phrases and proper names, respectively. When applied to the whole data set the feature produced a smaller but still significant improvement.