In this paper, we present a system that automatically generates questions from natural language text using discourse connectives. We explore the usefulness of the discourse connectives for Question Generation (QG) that looks at the problem beyond sentence level. Our work divides the QG task into content selection and question formation. Content selection consists of finding the relevant part in text to frame question from while question formation involves sense disambiguation of the discourse connectives, identification of question type and applying syntactic transformations on the content. The system is evaluated manually for syntactic and semantic correctness.
On the other hand, REF considered the question generation problem beyond sentence level and proposed an approach that uses discourse connectives to generate questions from a given text.
Automatic Question Generation using Discourse Cues
Proceedings of the Sixth Workshop on Innovative Use of NLP for Building Educational Applications
Computer Science