Reasoning about RoboCup soccer narratives

Hannaneh Hajishirzi, Julia Hockenmaier, Erik T. Mueller, Eyal Amir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings of the 27th Conference on Uncertainty in Artificial Intelligence, UAI 2011
PublisherAUAI Press
Pages291-300
Number of pages10
StatePublished - 2011

Publication series

NameProceedings of the 27th Conference on Uncertainty in Artificial Intelligence, UAI 2011

ASJC Scopus subject areas

  • Applied Mathematics
  • Artificial Intelligence

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