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We propose novel radical features from automatic translation for event extraction. Event detection is a complex language processing task for which it is expensive to collect training data, making generalisation challenging. We derive meaningful subword features from automatic translations into target language. Results suggest this method is particularly useful when using languages with writing systems that facilitate easy decomposition into subword features, e.g., logograms and Cangjie. Thedoi:10.18653/v1/p17-2046 dblp:conf/acl/WeiKNH17 fatcat:lbut7nu6afcm5o4deordmzcl4i