Combining Text Mining Techniques for QA4MRE 2013

This paper describes a lexical system developed for the main task of Question Answering for Machine Reading Evaluation 2013 (QA4MRE). The presented system executes the preprocessing of test documents, and generates hypotheses consisting of the question text combined with text from possible answers for the question. The hypotheses are compared to sentences from the text by the means of a set similarity measure. The k best similarity scores obtained by each hypothesis are averaged as ranking score for the hypothesis. Two variations of the developed system were utilized, one of them employing coreference detection and resolution techniques in order to take advantage of the discourse structure on the question answering process. The results generated by the systems in QA4MRE 2013 edition are presented and analyzed. The presented system should serve as a solid base for the development of a semantic approach on the task.