Answering Complex Questions by Combining Information from Curated and Extracted Knowledge Bases

Abstract

Knowledge-based question answering (KB-QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB. In this work, we look at answering complex questions which often require combining information from multiple sources. We present a novel KB-QA system, MULTIQUE, which can map a complex question to a complex query pattern using a sequence of simple queries each targeted at a specific KB. It finds simple queries using a neural-network based model capable of collective inference over textual relations in extracted KB and ontological relations in curated KB. Experiments show that our proposed system outperforms previous KB-QA systems on benchmark datasets, ComplexWebQuestions and WebQuestionsSP. * NB and XZ contributed equally to this work. 2. What college did the author of 'The Hobbit' attend? nesting 3. Which Portuguese speaking countries import fish from Brazil? conjunction 1. Where was Rihanna born? simple