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Choosing a set of coherence relations for text generation: A data-driven approach

  • Issues in Discourse or Text Planning
  • Conference paper
  • First Online:
Trends in Natural Language Generation An Artificial Intelligence Perspective (EWNLG 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1036))

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Abstract

An active research programme in Natural Language Generation has grown up around the notion of ‘coherence relations’. Relations are being used in a variety of roles in generation systems, in planning the structure of messages and in guiding their linguistic realisation. However, a confusing diversity exists between systems with respect to the particular relations they use.

This paper outlines a systematic methodology for justifying a set of relations, on the basis of the cue phrases that can be used to signal them explicitly in text. A large taxonomy of cue phrases has been gathered, from which a conception of relations as feature-based constructs is motivated. By considering small extracts from the taxonomy, individual features of relations can then be investigated in isolation. The paper concludes by noting some advantages of a feature-theoretic treatment of relations for NLG, as well as some problems with a reliance on cue phrases in a theory of text coherence.

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Author information

Authors and Affiliations

  1. Department of Artificial Intelligence, University of Edinburgh, 80 South Bridge, EH1 1HN, Edinburgh, Scotland

    Alistair Knott

  2. Microsoft Institute, 65 Epping Road, 2113, North Ryde, NSW, Australia

    Robert Dale

Authors
  1. Alistair Knott
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  2. Robert Dale
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Giovanni Adorni Michael Zock

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© 1996 Springer-Verlag Berlin Heidelberg

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Knott, A., Dale, R. (1996). Choosing a set of coherence relations for text generation: A data-driven approach. In: Adorni, G., Zock, M. (eds) Trends in Natural Language Generation An Artificial Intelligence Perspective. EWNLG 1993. Lecture Notes in Computer Science, vol 1036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60800-1_23

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  • DOI: https://doi.org/10.1007/3-540-60800-1_23

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60800-4

  • Online ISBN: 978-3-540-49457-7

  • eBook Packages: Springer Book Archive

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