Investigating the causal relation in informative texts

Abstract

Our work investigates the causal relation as it is expressed in informative texts. We view causal relations as important because of the dynamic dimension they bring to a domain model. Thorough study of a corpus leads us to distinguish two prominent classes of indicators of the causal relation: conjunctional phrases, and verbs. This paper identifies multiple knowledge-rich patterns within each class and studies their usage, frequency and noise. Results from this manual investigation informs a discussion on the feasibility of automatic extraction of the different forms of expression of the causal relation.