Question-Answering based on virtually integrated lexical knowledge base

This paper proposes an algorithm for causality inference based on a set of lexical knowledge bases that contain information about such items as event role, is-a hierarchy, relevant relation, antonymy, and other features. These lexical knowledge bases have mainly made use of lexical features and symbols in HowNet. Several types of questions are experimented to test the effectiveness of the algorithm here proposed. Particularly in this paper, the question form of “why” is dealt with to show how causality inference works.

• Type: Conference
• Year: 2003
• Where: IRAL
• Authors: Key-Sun Choi, Jae-Ho Kim, Masaru Miyazaki, Jun Goto, Yeun-Bae Kim
• Keywords: Causality Inference, Information Retrieval, IRAL 2003, Lexical Features, Lexical Knowledge Bases