Paper: Bilingual Event Extraction: a Case Study on Trigger Type Determination

ACL ID P14-2136
Title Bilingual Event Extraction: a Case Study on Trigger Type Determination
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Event extraction generally suffers from the data sparseness problem. In this paper, we address this problem by utilizing the labeled data from two different languages. As a pre- liminary study, we mainly focus on the sub- task of trigger type determination in event extraction. To make the training data in dif- ferent languages help each other, we pro- pose a uniform text representation with bi- lingual features to represent the samples and handle the difficulty of locating the triggers in the translated text from both monolingual and bilingual perspectives. Empirical studies demonstrate the effectiveness of the pro- posed approach to bilingual classification on trigger type determination. ?