Causal relation recognition between sentence-based events

Identifying causal relations between events in news reports has always been an important research issue, with the fact that recognizing causal relations can help us get a clearer view of the event evolution, and also help making predictions and decisions. This paper proposes a method to recognize causal relations in news reports, which consists of event extraction using trigger list, causal relation determination based on specific judgment rules, and finally a 2-dimensional SVM classification. Experiments which mainly focus on the new labor law related news reports have shown that this method works effectively on this issue, and get a precision of 93% on an open corpus for testing.