Automatic Question Generation Based on Analysis of Sentence Structure

Miroslav Blsták, Viera Rozinajová

Abstract: This paper presents a novel approach to the area of automated factual question generation. We propose a template-based method which uses the structure of sentences to create multiple sentence patterns on various levels of abstraction. The pattern is used to classify the sentences and to generate questions. Our approach allows to create questions on different levels of difficulty and generality e.g. from general questions to specific ones. Other advantages lie in simple expansion of patterns and in increasing the text coverage. We also suggest a new way of storing patterns which significantly improves pattern matching process. Our first results indicate that the proposed method can be an interesting direction in the research of automated question generation.