@inproceedings{wei-king-2024-sense-day,
title = "Sense of the Day: Short Timeframe Temporal-Aware Word Sense Disambiguation",
author = "Wei, Yuchen and
King, Milton",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1278",
pages = "14676--14686",
abstract = "The predominant sense of a lemma can vary based on the timeframe (years, decades, centuries) that the text was written. In our work, we explore the predominant sense of shorter timeframes (days, months, seasons, etc.) and find that different short timeframes can have different predominant senses from each other and from the predominant sense of a corpus. Leveraging the predominant sense and sense distribution of a short timeframe, we design short timeframe temporal-aware word sense disambiguation (WSD) models that outperform a temporal agnostic model. Likewise, author-aware WSD models tend to outperform author agnostic models, therefore we augment our temporal-aware models to leverage knowledge of author-level predominant senses and sense distributions to create temporal and author-aware WSD models. In addition to this, we found that considering recent usages of a lemma by the same author can assist a WSD model. Our approach requires the use of only a small amount of text from authors and timeframes.",
}
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<abstract>The predominant sense of a lemma can vary based on the timeframe (years, decades, centuries) that the text was written. In our work, we explore the predominant sense of shorter timeframes (days, months, seasons, etc.) and find that different short timeframes can have different predominant senses from each other and from the predominant sense of a corpus. Leveraging the predominant sense and sense distribution of a short timeframe, we design short timeframe temporal-aware word sense disambiguation (WSD) models that outperform a temporal agnostic model. Likewise, author-aware WSD models tend to outperform author agnostic models, therefore we augment our temporal-aware models to leverage knowledge of author-level predominant senses and sense distributions to create temporal and author-aware WSD models. In addition to this, we found that considering recent usages of a lemma by the same author can assist a WSD model. Our approach requires the use of only a small amount of text from authors and timeframes.</abstract>
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%0 Conference Proceedings
%T Sense of the Day: Short Timeframe Temporal-Aware Word Sense Disambiguation
%A Wei, Yuchen
%A King, Milton
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F wei-king-2024-sense-day
%X The predominant sense of a lemma can vary based on the timeframe (years, decades, centuries) that the text was written. In our work, we explore the predominant sense of shorter timeframes (days, months, seasons, etc.) and find that different short timeframes can have different predominant senses from each other and from the predominant sense of a corpus. Leveraging the predominant sense and sense distribution of a short timeframe, we design short timeframe temporal-aware word sense disambiguation (WSD) models that outperform a temporal agnostic model. Likewise, author-aware WSD models tend to outperform author agnostic models, therefore we augment our temporal-aware models to leverage knowledge of author-level predominant senses and sense distributions to create temporal and author-aware WSD models. In addition to this, we found that considering recent usages of a lemma by the same author can assist a WSD model. Our approach requires the use of only a small amount of text from authors and timeframes.
%U https://aclanthology.org/2024.lrec-main.1278
%P 14676-14686
Markdown (Informal)
[Sense of the Day: Short Timeframe Temporal-Aware Word Sense Disambiguation](https://aclanthology.org/2024.lrec-main.1278) (Wei & King, LREC-COLING 2024)
ACL