Event extraction is a particularly chalenging type of information extraction (IE). Most curent event extraction systems rely on local information at the phrase or sentence level. However, this local context may be insuficient to resolve ambiguities in identifying particular types of events; information from a wider scope can serve to resolve some of these ambiguities. In this paper, we use document level information to improve the performance of ACE event extraction. In contrast to previous work, we do not limit ourselves to information about events of the same type, but rather use information about other types of events to make predictions or resolve ambiguities regarding a given event. W lern sch relationships from the training corpus and use them to help predict the o...

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