From local to global coherence: a bottom-up approach to text planning

  • Authors:
  • Daniel Marcu

  • Affiliations:
  • Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

  • Venue:
  • AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
  • Year:
  • 1997

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Abstract

We present a new, data-driven approach to text planning, which can be used not only to map full knowledge pools into natural language texts, but also to generate texts that satisfy multiple, high-level communicative goals. The approach explains how global coherence can be achieved by exploiting the local coherence constraints of rhetorical relations. The local constraints were derived from a corpus analysis.