The DI@UE’s participation in QA4MRE: from QA to multiple choice challenge

Abstract

This QA4MRE edition brought two challenges to the DI@UE team: the absence of Portuguese as a working language and the different nature of the task when compared with previous participation in QA@CLEF. We addressed this multiple choice answering problem by assessing answer candidates in a text surface based manner, without a deep linguistic processing. This system employs a Lucene based search engine and Wordnet to assist in synonym check and morphological normalization. Answer analysis and the criteria for the answering decision are fun- damentally based on superficial analysis of document text, enriched with semantic validation of compatibility between terms. The solution we describe answered to 73 from 120 questions, having 18 correct answers and an accuracy of 0.15.