AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling

Fuente: arXiv
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Autori principali: Fedorova, Mariia, Mickus, Timothee, Partanen, Niko, Siewert, Janine, Spaziani, Elena, Kutuzov, Andrey
Natura: Preprint
Pubblicazione: 2024
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author Fedorova, Mariia
Mickus, Timothee
Partanen, Niko
Siewert, Janine
Spaziani, Elena
Kutuzov, Andrey
author_facet Fedorova, Mariia
Mickus, Timothee
Partanen, Niko
Siewert, Janine
Spaziani, Elena
Kutuzov, Andrey
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2407_04079
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling
Fedorova, Mariia
Mickus, Timothee
Partanen, Niko
Siewert, Janine
Spaziani, Elena
Kutuzov, Andrey
Computation and Language
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.
title AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling
topic Computation and Language
url https://arxiv.org/abs/2407.04079