Extraction of Causal Knowledge from Articles Concerning Business Performance of Companies

Abstract

This paper proposes a method that extracts causal knowledge from Japanese financial articles concerning business performance of companies via clue expressions. Our method decides whether a sentence includes causal knowledge or not when the method extracts it. For example, a sentence fragment "World economy recession due to the subprime loan crisis ..." contains causal knowledge in which \World economy recession" is an effect phrase and \the subprime loan crisis" is its cause phrase. These relations are found by clue phrases,such as "ため(tame: because)" and "により(niyori: due to)". We found that some specific syntactic patterns are useful to improve accuracy of extracting causal knowledge. Therefore, our method can extract causal knowledge accurately.