Capturing negation in question answering systems

Abstract

This masters thesis will present my research on the world of Negation, as well as my attempt to apply the Negation Algorithm on a new Question Answering system which is able to accept negative input in natural language. The aim of this project is to focus on the uses of negation in natural language, and on the importance of including negative constructions in Information Retrieval processes, which for the moment treat negation as a nonexisting phenomenon in natural language. The new restricted-domain question answering system is called NotFilms, and accepts subject and object questions regarding Movies of 2005. NotFilms reads the input in natural language, produces its semantic representation, applies the IR algorithm on the semantic reading, and provides the user with the exact answer. It allows the existence of the negative particle ’not’ in the input, and as long as the input can be semantically represented by the linguistic processes of the system, it answers both affirmative and negative questions with the same efficiency. Results have shown that the linguistic and IR processes of the system can give relevant answers for 75% of the users’ questions.