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  Automated identification of borrowings in multilingual wordlists

List, J.-M., & Forkel, R. (2021). Automated identification of borrowings in multilingual wordlists. Open Research Europe, 1: 79. doi:10.12688/openreseurope.13843.2.

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List_Automated_OpenResEuro_2021.pdf (Publisher version), 6MB
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List_Automated_OpenResEuro_2021.pdf
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© 2021 List J and Forkel R. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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List_Automated_OpenResEuro_Dataset_2021.zip (Supplementary material), 68MB
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 Creators:
List, Johann-Mattis1, Author                 
Forkel, Robert1, Author                 
Affiliations:
1Department of Linguistic and Cultural Evolution, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, Deutscher Platz 6, 04103 Leipzig, DE, ou_3237541              

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 Abstract: Although lexical borrowing is an important aspect of language evolution, there have been few attempts to automate the identification of borrowings in lexical datasets. Moreover, none of the solutions which have been proposed so far identify borrowings across multiple languages. This study proposes a new method for the task and tests it on a newly compiled large comparative dataset of 48 South-East Asian languages from Southern China. The method yields very promising results, while it is conceptually straightforward and easy to apply. This makes the approach a perfect candidate for computer-assisted exploratory studies on lexical borrowing in contact areas.

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Language(s): eng - English
 Dates: 2021-082021
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.12688/openreseurope.13843.2
 Degree: -

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Project name : CALC
Grant ID : 715618
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: Open Research Europe
Source Genre: Journal
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Publ. Info: The European Commission
Pages: - Volume / Issue: 1 Sequence Number: 79 Start / End Page: - Identifier: ISSN: 2732-5121