Predicting the Presence of Discourse Connectives

Gary Patterson, Andrew Kehler

Abstract: We present a classification model that predicts the presence or omission of a lexical connective between two clauses, based upon linguistic features of the clauses and the type of discourse relation holding between them. The model is trained on a set of high frequency relations extracted from the Penn Discourse Treebank and achieves an accuracy of 86.6%. Analysis of the results reveals that the most informative features relate to the discourse dependencies between sequences of coherence relations in the text. We also present results of an experiment that provides insight into the nature and difficulty of the task.