  Script knowledge plays a central role in text understanding and is relevant
for a variety of downstream tasks. In this paper, we consider two recent
datasets which provide a rich and general representation of script events in
terms of paraphrase sets. We introduce the task of mapping event mentions in
narrative texts to such script event types, and present a model for this task
that exploits rich linguistic representations as well as information on
temporal ordering. The results of our experiments demonstrate that this complex
task is indeed feasible.
