Ellipsis and Coreference Resolution in a Computerized Virtual Patient Dialogue System

Abstract

This paper describes the design of an ellipsis and coreference resolution module integrated in a computerized virtual patient dialogue system. Real medical diagnosis dialogues have been collected and analyzed. Several groups of diagnosis-related concepts were defined and used to construct rules, patterns, and features to detect and resolve ellipsis and coreference. The best F-scores of ellipsis detection and resolution were 89.15 % and 83.40 %, respectively. The best F-scores of phrasal coreference detection and resolution were 93.83 % and 83.40 %, respectively. The accuracy of pronominal anaphora resolution was 92 % for the 3rd-person singular pronouns referring to specific entities, and 97.31 % for other pronouns.