Reasoning about RoboCup Soccer Narratives
  This paper presents an approach for learning to translate simple narratives,
i.e., texts (sequences of sentences) describing dynamic systems, into coherent
sequences of events without the need for labeled training data. Our approach
incorporates domain knowledge in the form of preconditions and effects of
events, and we show that it outperforms state-of-the-art supervised learning
systems on the task of reconstructing RoboCup soccer games from their
commentaries.
