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.
AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling / Fedorova, Mariia; Mickus, Timothee; Partanen, Niko; Siewert, Janine; Spaziani, Elena; Kutuzov, Andrey. - (2024). (Intervento presentato al convegno 5th International Workshop on Computational Approaches to Historical Language Change (LChange’24) tenutosi a Bangkok, Thailand).
AXOLOTL'24 Shared Task on Multilingual Explainable Semantic Change Modeling
Elena Spaziani;
2024
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
