@inproceedings{dinu-etal-2024-takes,
title = "It takes two to borrow: a donor and a recipient. Who{'}s who?",
author = "Dinu, Liviu and
Uban, Ana and
Dinu, Anca and
Iordache, Ioan-Bogdan and
Georgescu, Simona and
Zoicas, Laurentiu",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Findings of the Association for Computational Linguistics ACL 2024",
month = aug,
year = "2024",
address = "Bangkok, Thailand and virtual meeting",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-acl.360",
pages = "6023--6035",
abstract = "We address the open problem of automatically identifying the direction of lexical borrowing, given word pairs in the donor and recipient languages. We propose strong benchmarks for this task, by applying a set of machine learning models. We extract and publicly release a comprehensive borrowings dataset from the recent RoBoCoP cognates and borrowings database for five Romance languages. We experiment on this dataset with both graphic and phonetic representations and with different features, models and architectures. We interpret the results, in terms of F1 score, commenting on the influence of features and model choice, of the imbalanced data and of the inherent difficulty of the task for particular language pairs. We show that automatically determining the direction of borrowing is a feasible task, and propose additional directions for future work.",
}
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<abstract>We address the open problem of automatically identifying the direction of lexical borrowing, given word pairs in the donor and recipient languages. We propose strong benchmarks for this task, by applying a set of machine learning models. We extract and publicly release a comprehensive borrowings dataset from the recent RoBoCoP cognates and borrowings database for five Romance languages. We experiment on this dataset with both graphic and phonetic representations and with different features, models and architectures. We interpret the results, in terms of F1 score, commenting on the influence of features and model choice, of the imbalanced data and of the inherent difficulty of the task for particular language pairs. We show that automatically determining the direction of borrowing is a feasible task, and propose additional directions for future work.</abstract>
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%0 Conference Proceedings
%T It takes two to borrow: a donor and a recipient. Who’s who?
%A Dinu, Liviu
%A Uban, Ana
%A Dinu, Anca
%A Iordache, Ioan-Bogdan
%A Georgescu, Simona
%A Zoicas, Laurentiu
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand and virtual meeting
%F dinu-etal-2024-takes
%X We address the open problem of automatically identifying the direction of lexical borrowing, given word pairs in the donor and recipient languages. We propose strong benchmarks for this task, by applying a set of machine learning models. We extract and publicly release a comprehensive borrowings dataset from the recent RoBoCoP cognates and borrowings database for five Romance languages. We experiment on this dataset with both graphic and phonetic representations and with different features, models and architectures. We interpret the results, in terms of F1 score, commenting on the influence of features and model choice, of the imbalanced data and of the inherent difficulty of the task for particular language pairs. We show that automatically determining the direction of borrowing is a feasible task, and propose additional directions for future work.
%U https://aclanthology.org/2024.findings-acl.360
%P 6023-6035
Markdown (Informal)
[It takes two to borrow: a donor and a recipient. Who’s who?](https://aclanthology.org/2024.findings-acl.360) (Dinu et al., Findings 2024)
ACL
- Liviu Dinu, Ana Uban, Anca Dinu, Ioan-Bogdan Iordache, Simona Georgescu, and Laurentiu Zoicas. 2024. It takes two to borrow: a donor and a recipient. Who’s who?. In Findings of the Association for Computational Linguistics ACL 2024, pages 6023–6035, Bangkok, Thailand and virtual meeting. Association for Computational Linguistics.