INAOE-UPV Joint Participation in CLEF 2005: Experiments in Monolingual Question Answering

Recent works on question answering are based on complex natural language processing techniques: named entity extractors, parsers, chunkers, etc. While these approaches have proven to be effective they have the disadvantage of being targeted to a particular language. In this paper we present a full datadriven method that uses simple lexical pattern matching and statistical techniques in order to identify the relevant passages as well as the more probable candidate answers for factual and definition questions. The main quality of this method is that it can be applied to different languages without requiring major adaptation changes. Experimental results of the method in Spanish, Italian and French show that the approach can be a practical solution for monolingual and multilingual question answering applications.