Discourse Element Identification in Student Essays based on Global and Local Cohesion

Abstract

We present a method of using cohesion to improve discourse element identification for sentences in student essays. New features for each sentence are derived by considering its relations to global and local cohesion, which are created by means of cohesive resources and subtopic coverage. In our experiments, we obtain significant improvements on identifying all discourse elements, especially of +5% F1 score on thesis and main idea. The analysis shows that global cohesion can better capturethesis statements.