License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/OASIcs.LDK.2021.32
URN: urn:nbn:de:0030-drops-145681
URL: https://drops.dagstuhl.de/opus/volltexte/2021/14568/
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Hesse, Christoph ; Langner, Maurice ; Benz, Anton ; Klabunde, Ralf

Discrepancies Between Database- and Pragmatically Driven NLG: Insights from QUD-Based Annotations

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OASIcs-LDK-2021-32.pdf (0.5 MB)


Abstract

We present annotation findings when using an annotated corpus of driving reports as informational texts with an elaborated pragmatics for the automatic generation of corresponding texts. The generation process requires access to a database providing the technical details of the vehicles, as well as an annotated corpus for sophisticated, pragmatically motivated text planning. We focus on the annotation results since they are the basic framework for linking text planning with database queries and microplanning. We show that the annotations point to a variety of linguistic phenomena that have received little or no attention in the literature so far, and they raise corresponding questions regarding the access to information from databases for the generation process.

BibTeX - Entry

@InProceedings{hesse_et_al:OASIcs.LDK.2021.32,
  author =	{Hesse, Christoph and Langner, Maurice and Benz, Anton and Klabunde, Ralf},
  title =	{{Discrepancies Between Database- and Pragmatically Driven NLG: Insights from QUD-Based Annotations}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{32:1--32:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/14568},
  URN =		{urn:nbn:de:0030-drops-145681},
  doi =		{10.4230/OASIcs.LDK.2021.32},
  annote =	{Keywords: NLG, question-under-discussion analysis, information structure, database retrieval}
}

Keywords: NLG, question-under-discussion analysis, information structure, database retrieval
Collection: 3rd Conference on Language, Data and Knowledge (LDK 2021)
Issue Date: 2021
Date of publication: 30.08.2021
Supplementary Material: Software (Source Code): https://github.com/MMLangner/QUDA


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