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 NPand 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.

• Type: Conference
• Year: 2003
• Where: ACL
• Authors: Michael Strube, Christoph Müller
• Keywords: ACL 2003, ACL 2007, Pronoun Resolution, Spoken Dialogue, Tree Based Approach