Fact-based question decomposition for candidate answer re-ranking

Factoid questions often contain one or more assertions (facts) about their answers. However, existing question-answering (QA) systems have not investigated how the multiple facts may be leveraged to enhance system performance. We argue that decomposing complex factoid questions can benefit QA, as an answer candidate is more likely to be correct if multiple independent facts support it. We categorize decomposable questions as parallel or nested, depending on processing strategy required. We present a novel decomposition framework—for parallel and nested questions—which can be overlaid on top of traditional QA systems. It contains decomposition rules for identifying fact sub-questions, a question-rewriting component and a candidate re-ranker. In a particularly challenging domain for our baseline QA system, our framework shows a statistically significant improvement in end-to-end QA performance. Categories and Subject Descriptors I.2.7 [Artificial Intelligence]: Natural Language P...

• Type: Journal
• Year: 2011
• Where: CIKM
• Authors: Aditya Kalyanpur, Siddharth Patwardhan, Branimir Boguraev, Adam Lally, Jennifer Chu-Carroll
• Keywords: CIKM 2011, Information Technology, Natural Language Processing, Performance Categories, QA Systems