Papers › Multilingual Normalization of Temporal Expressions with Masked Language Models

Multilingual Normalization of Temporal Expressions with Masked Language Models

20 May 2022arXiv:2205.10399archive 2025-07-28

Lukas Lange, Jannik Strötgen, Heike Adel, Dietrich Klakow

The detection and normalization of temporal expressions is an important task and preprocessing step for many applications. However, prior work on normalization is rule-based, which severely limits the applicability in real-world multilingual settings, due to the costly creation of new rules. We propose a novel neural method for normalizing temporal expressions based on masked language modeling. Our multilingual method outperforms prior rule-based systems in many languages, and in particular, for low-resource languages with performance improvements of up to 33 F1 on average compared to the state of the art.

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boschresearch/temporal-tagging-eacl officialmentioned in papermentioned on GitHubpytorch report

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Language ModelingLanguage ModellingMasked Language Modeling

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