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Lexical semantic change discovery

  • While there is a large amount of research in the field of Lexical Semantic Change Detection, only few approaches go beyond a standard benchmark evaluation of existing models. In this paper, we propose a shift of focus from change detection to change discovery, i.e., discovering novel word senses over time from the full corpus vocabulary. By heavily fine-tuning a type-based and a token-based approach on recently published German data, we demonstrate that both models can successfully be applied to discover new words undergoing meaning change. Furthermore, we provide an almost fully automated framework for both evaluation and discovery.

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Author:Sinan Kurtyigit, Maike ParkORCiD, Dominik Schlechtweg, Jonas KuhnGND, Sabine Schulte im WaldeORCiDGND
Parent Title (English):Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Publisher:Association for Computational Linguistics
Place of publication:Stroudsburg
Editor:Chengqing Zong, Fei Xia, Wenjie Li, Roberto Navigli
Document Type:Conference Proceeding
Year of first Publication:2021
Date of Publication (online):2021/09/24
Publishing Institution:Leibniz-Institut f√ľr Deutsche Sprache (IDS)
GND Keyword:Deutsch; Korpus <Linguistik>; Semantik; Semasiologie; Sprachwandel; Wortschatz
First Page:6985
Last Page:6998
DDC classes:400 Sprache / 400 Sprache, Linguistik
Open Access?:ja
Leibniz-Classification:Sprache, Linguistik
Linguistics-Classification:Lexikologie / Etymologie
Program areas:L1: Lexikographie und Sprachdokumentation
Licence (English):License LogoCreative Commons - Attribution 4.0 International