This paper describes one part of an exploration into how this information can be captured automatically.
we have developed annotation guidelines to minimize discrepant judgments and annotated 58 articles, comprising 2288 events; we have developed a method for measuring inter-annotator agreement when the judgments are intervals on a scale; and we have shown that machine learning techniques applied to the annotated data considerably out-perform a baseline and approach human performance.