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Increasing cohesion in automatically generated natural language texts

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Advances in Artificial Intelligence (AI*IA 1993)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 728))

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Abstract

In this paper we show how the quality of machine-generated texts can be improved by augmenting a text planner with sophisticated components for the generation of textual phenomena. We discuss this point by introducing an example from our corpus of texts as so far generated by the schema-based planner RSE. We then describe the weaknesses of schematic approaches and show how a hybrid text planning architecture, which includes techniques to flexibly generate links between discourse units eliminates those disadvantages. Finally, we will show how the hybrid architecture adopted from [7] has been changed and extended in order to treat thematic progression and to generate referring expressions.

We would like to thank Lee Fedder, Oliviero Stock and Carlo Strapparava for comments on a previous version of this paper.

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Authors and Affiliations

  1. Istituto per la Ricerca Scientifica e Tecnologica (IRST), 38050, Trento-Povo, Italy

    Elisabeth A. Maier & Elena Not

Authors
  1. Elisabeth A. Maier
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  2. Elena Not
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Pietro Torasso

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© 1993 Springer-Verlag Berlin Heidelberg

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Maier, E.A., Not, E. (1993). Increasing cohesion in automatically generated natural language texts. In: Torasso, P. (eds) Advances in Artificial Intelligence. AI*IA 1993. Lecture Notes in Computer Science, vol 728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57292-9_62

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  • DOI: https://doi.org/10.1007/3-540-57292-9_62

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57292-3

  • Online ISBN: 978-3-540-48038-9

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