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

Authors Christoph Hesse, Maurice Langner, Anton Benz, Ralf Klabunde

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Author Details

Christoph Hesse
  • Leibniz-Zentrum Allgemeine Sprachwissenschaft, Berlin, Germany
Maurice Langner
  • Department of Linguistics, Ruhr-University Bochum, Germany
Anton Benz
  • Leibniz-Zentrum Allgemeine Sprachwissenschaft, Berlin, Germany
Ralf Klabunde
  • Department of Linguistics, Ruhr-University Bochum, Germany

Funding

This work has been supported by the Deutsche Forschungsgemeinschaft, project "Propositional and Non-at-issue Content in Text Generation: Exploring the QUD–Perspective", grants AB 4348/5-1; KL 1109/7-1.

Cite AsGet BibTex

Christoph Hesse, Maurice Langner, Anton Benz, and Ralf Klabunde. Discrepancies Between Database- and Pragmatically Driven NLG: Insights from QUD-Based Annotations. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 32:1-32:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/OASIcs.LDK.2021.32

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.

Subject Classification

ACM Subject Classification
  • Applied computing → Arts and humanities
Keywords
  • NLG
  • question-under-discussion analysis
  • information structure
  • database retrieval

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References

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