NTT's Question Answering System for NTCIR-6 QAC-4

NTCIR-6 QAC-4 organizers announced that there would be no restriction (such as factoid) on QAC4 questions, but they plan to include many 'definition' questions and 'why' questions. Therefore, we focused on these two question types. For 'definition' questions, we used a simple pattern-based approach. For 'why' questions, hand-crafted rules were used in previous work for answer candidate extraction (5). However, such rules greatly depend on developers' intuition and are costly to make. We adopt a supervised machine learning approach. We collected causal expressions from the EDR corpus and trained a causal expression classifier, integrating lexical, syntactic, and semantic features. The experimental results show that our sys- tem is effective for 'why' and 'definition' questions.