A Machine Learning Approach to Pronoun Resolution in Spoken Dialogue 
 We apply a decision tree based approach to pronoun resolution in spoken dialogue . Our system deals with pronouns with NP- and non-NP-antecedents . We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features . We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron's (2002) manually tuned system . 