Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/104642
Title: Overview of the CLEF 2022 JOKER Task 1 : Classify and Explain Instances of Wordplay
Other Titles: Proceedings of the Working Notes of CLEF
Authors: Ermakova, Liana
Regattin, Fabio
Miller, Tristan
Bosser, Anne-Gwenn
Araújo, Sílvia
Borg, Claudine
Corre, Gaelle Le
Boccou, Julien
Digue, Albin
Damoy, Aurianne
Campen, Paul
Puchalski, Orlane
Keywords: Computational linguistics
Puns and punning -- Translating
Classification
Plays on words
Deep learning (Machine learning)
Issue Date: 2022
Publisher: Rheinisch-Westfaelische Technische Hochschule Aachen. Lehrstuhl Informatik V
Citation: Ermakova, L., Regattin, F., Miller, T., Bosser, A. G., Araújo, S., Borg, C., ... & Puchalski, O. (2022). Overview of the CLEF 2022 JOKER Task 1: Classify and explain instances of wordplay. In. G. Faggioli, N. Ferro, A. Hanbury, M. Potthastet (Eds.), Proceedings of the Working Notes of CLEF (pp. 1641-1665). Aachen: Rheinisch-Westfaelische Technische Hochschule Aachen. Lehrstuhl Informatik V
Abstract: As a multidisciplinary field of study, humour remains one of the most difficult aspects of intercultural communication. Understanding humor often involves understanding implicit cultural references and/or double meanings, which raises the questions of how to detect and classify instances of this complex phenomenon. This paper provides an overview of Pilot Task 1 of the CLEF 2022 JOKER track, where participants had to classify and explain instances of wordplay. We introduce a new classification of wordplay and a new annotation scheme for wordplay interpretation suitable both for phrase-based wordplay and wordplay in named entities. We describe the collection of our data, our task setup, and the evaluation procedure, and we give a brief overview of the participating teams’ approaches and results.
URI: https://www.um.edu.mt/library/oar/handle/123456789/104642
ISSN: 16130073
Appears in Collections:Scholarly Works - FacArtTTI

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