摘要
The goal of Event extraction is to extract structured information of events that are of interest from unstructured documents. Existing event extractors for social media suffer from two major problems: lack of context and informal nature. In this paper, instead of conducting event extraction solely on each social media message, we incorporate cross-genre knowledge to boost the event extractor performance. Experiment results demonstrate that without any additional annotations, our proposed approach is able to provide 15% absolute F-score improvement over the state-of-the-art.