Chris Welty and I presented at the Derive2012 workshop, in conjunction with ISWC2012 Conference our paper focussing on how events can be detected & extracted from natural language text, and how those are represented for use on the semantic web. We draw an inspiration from the similarity between crowdsourcing approaches for tagging and text annotation task for ground truth of events. Thus, we propose a novel approach that harnesses the disagreement between the human annotators by defining a framework to capture and analyze the nature of the disagreement. We expect two novel results from this approach. On the one hand, achieving a new way of measuring ground truth (performance), and on the other hand identifying a new set of semantic features for learning in event extraction.
Other work on events extraction in the history domain with cultural heritage data I am doing in the context of the Agora project.
You can find the data and the paper @figshare
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