Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/10323

Title: An Approach to the Main Task of QA4MRE-2013
Authors: Santos, Marília
Saias, José
Quaresma, Paulo
Editors: Forner, Pamela
Navigli, Roberto
Tufis, Dan
Keywords: Question Answering
NLP
Machine Reading
Issue Date: Sep-2013
Publisher: clef2013.org
Citation: Marilia Santos, Jose Saias, and Paulo Quaresma. An approach to the main task of qa4mre-2013. In Pamela Forner, Roberto Navigli, and Dan Tufis, editors, CLEF 2013 Evaluation Labs and Workshop Online Working Notes - Question Answering for Machine Reading Evaluation (QA4MRE), Valencia, Spain, September 2013. ISBN 978-88-904810-5-5.
Abstract: 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.
URI: http://www.clef-initiative.eu/documents/71612/75d1893f-1714-487d-a641-353ec8d86063
http://hdl.handle.net/10174/10323
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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