Article ID Journal Published Year Pages File Type
395897 Information Sciences 2009 16 Pages PDF
Abstract

This paper describes a new advance in solving Cross-Lingual Question Answering (CL–QA) tasks. It is built on three main pillars: (i) the use of several multilingual knowledge resources to reference words between languages (the Inter Lingual Index (ILI) module of EuroWordNet and the multilingual knowledge encoded in Wikipedia); (ii) the consideration of more than only one translation per word in order to search candidate answers; and (iii) the analysis of the question in the original language without any translation process. This novel approach overcomes the errors caused by the common use of Machine Translation (MT) services by CL–QA systems. We also expose some studies and experiments that justify the importance of analyzing whether a Named Entity should be translated or not. Experimental results in bilingual scenarios show that our approach performs better than an MT based CL–QA approach achieving an average improvement of 36.7%.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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