Prof. Dr. Ralf Klabunde

ralf.klabunde@rub.de +49 234 32-22460

GB 1/151

Profile

I am a linguist who works on pragmatic effects in communication. I am especially interested in formal models of information exchange and their use in natural language generation and dialogue systems. I teach at the Department of Linguistics and LDSL.

Pragmatics

Past semesters

WiSe 20/21

  • Computerlinguistisches Propädeutikum
  • Einführung in die Semantik
  • Markov Models for Dialogue Processing
  • Aspekte der Textstrukturierung

SoSe 2020

Sabatical

Selected Publications

Hesse, C., Langner, M., Benz, A. und Klabunde, R. (2021) Discrepancies between database- and pragmatically driven NLG: Insights from QUD-based annotations. In: Proceedings of the 3rd Conference on Language, Data and Knowledge. Zaragoza.
Klabunde, R., Mihatsch, W. und Dipper, S. (2021) (Hrsg.) Linguistik im Sprachvergleich. Germanistik – Romanistik – Anglistik. Stuttgart: Metzler (ca. 800 S.).
Christoph Hesse, Maryam Mohammadi, Maurice Langner, Judith Fischer, Anton Benz, Ralf Klabunde. 2018. Communicating an understanding of intention: Speech act conditionals and modified numerals in a Q/A system. Proceedings of the 22nd Workshop on the Semantics and Pragmatics of Dialogue.
Klabunde. R. 2018. Formale Pragmatik. In: Liedke, Frank und Tuchen, Astrid. 2018. Handbuch Pragmatik; 122-131
J. Stevens, A. Benz, S. Reuße, & R. Klabunde. 2016. Pragmatic question answering: A game-theoretic approach. Data & Knowledge Engineering 106, 52-69.
J. Stevens, A. Benz, S. Reuße & R. Klabunde. 2015. A strategic reasoning model for generating alternative answers. Proceedings of the 53rd Annual Meeting of the ACL, 534-542.

Current Projects

Propositional and Non-at-issue Content in Text Generation: Exploring the QUD–Perspective (Funded by DFG - KL 1109/7-1, 2020-2022)

In this project, we investigate the descriptive and explanatory strength of
the QUD-approach for the generation of texts. Inverting the perspective - instead of reconstructing
the QUD structure for a given text we aim at generating a text, given a QUD structure - raises several
new theoretical, empirical and computationally motivated research questions.

Past Projects

Bayes'sche Ansätze für eine präferenzbasierte Antwortgenerierung im Dialog (2017-2018, KL 1109/6-2)