Constructing Event Templates from Written News

We propose a pipeline for learning event templates from a large corpus of textual news articles. An event template is a machine-usable semantic data structure, in our case a graph, describing a certain event type. Most earthquake news reports, for example, semantically fit the template "x people dead, town y shook, at time z". Such templates can be used as an input for information extraction tasks or automated ontology extension. We also present preliminary results in the form of sample extracted templates from Google News articles.