AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling

AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling

This paper describes the organization and findings of AXOLOTL'24, the first multilingual explainable semantic change modeling shared task. We present new sense-annotated diachronic semantic change datasets for Finnish and Russian which were employed in the shared task, along with a surprise tes...

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Bibliographic Details
Main Authors: Fedorova, Mariia, Mickus, Timothee, Partanen, Niko, Siewert, Janine, Spaziani, Elena, Kutuzov, Andrey
Format: Journal Article
Language:English
Published: 04-07-2024
Subjects:
Computer Science - Computation and Language
Online Access:Get full text
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Summary:This paper describes the organization and findings of AXOLOTL'24, the first multilingual explainable semantic change modeling shared task. We present new sense-annotated diachronic semantic change datasets for Finnish and Russian which were employed in the shared task, along with a surprise test-only German dataset borrowed from an existing source. The setup of AXOLOTL'24 is new to the semantic change modeling field, and involves subtasks of identifying unknown (novel) senses and providing dictionary-like definitions to these senses. The methods of the winning teams are described and compared, thus paving a path towards explainability in computational approaches to historical change of meaning.
DOI:10.48550/arxiv.2407.04079