An Approach to the Main Task of QA4MRE-2013

• Author(s): Santos, Marília ; Saias, José ; Quaresma, Paulo
• Date: 2013
• Persistent ID: http://hdl.handle.net/10174/10323
• Origin: Repositório Científico da Universidade de Évora
• Subject(s): Question Answering; NLP; Machine Reading
• Document Type: Article
• Language: English
• Editor(s): Forner, Pamela; Navigli, Roberto; Tufis, Dan

Description

This article describes the participation of a group from the University of Évora in the CLEF2013 QA4MRE main task. Our system has a superficial text analysis based approach. The methodology starts with the preprocessing of background collection documents, whose texts are lemmatized and then indexed. Named entities and numerical expressions are sought in questions and their candidate answers. Then the lemmatizer is applied and stop words are removed. Answer patterns are formed for each question+answer pair, with a search query for document retrieval. Original search terms are expanded with synonyms and hyperonyms. Finally, the texts retrieved for each candidate response are segmented and scored for answer selection. Considering only the main questions, the system best result was obtained in the third run, having answered to 206 questions, with 0.24 c@1 and 51 correct answers. When evaluating main and auxiliary questions, the final run continued to have our better results, being answered 245 questions, with 64 right answers and 0.26 for c@1. The use of hypernyms proved to be an improvement factor in the third run, which results had a 12% increase of correct answers and a 0.02 gain in c@1.