Event reference identification is often treated as a sentence level classification task. However, several different event references can occur within a single sentence. We present a set of experiments involving real world event reference identification at the word level in newspaper and newswire documents, addressing the issue of effective text representation for classification of events using support vector machines. Our final system achieved an F-score of 0.764, significantly exceeding that of our baseline system. Additionally we achieved a marginally higher performance than a more complex comparable system.
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