Extending an Indonesian Semantic Analysis-based Question Answering System with Linguistic and World Knowledge Axioms
Rahmad Mahendra, Septina Dian Larasati, Hendra Manurung · Institutional Repositories DataBase (IRDB) · 2008
Abstract. We adopt a previously developed model of deep syntactic and semantic processing to support question answering for Bahasa Indonesia, and extend it by adding a number of axioms designed to encode useful knowledge for answering questions, thus increasing the inferential power of the QA system. We believe this approach can increase the robustness of semantic analysis-based QA systems, whilst simultaneously lightening the burden of complexity in designing semantic attachment rules that transduce logical forms from syntactic structures. We show how these added axioms enable the system to answer questions which previously could not have been answered.