POS Tagging for the Endangered Dagur Language
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AKYITLGVL" target="_blank" >RIV/00216208:11320/25:KYITLGVL - isvavai.cz</a>
Výsledek na webu
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195953703&partnerID=40&md5=15722f6ea04aa240620c57ec2ecc43fa" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195953703&partnerID=40&md5=15722f6ea04aa240620c57ec2ecc43fa</a>
DOI - Digital Object Identifier
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Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
POS Tagging for the Endangered Dagur Language
Popis výsledku v původním jazyce
The application of natural language processing tools opens new ways for the documentation and revitalization of under-resourced languages. In this article we aim to investigate the feasibility of automatic part-of-speech (POS) tagging for Dagur, which is an endangered Mongolic language spoken mainly in northeast China, with no official written standard for all Dagur dialects. We present a new manually annotated corpus for Dagur, which includes about 1,200 tokens, and detail the decisions made during the annotation process. This corpus is used to test transfer of models from other languages, especially from Buryat, which is currently the only Mongolic language included in the Universal Dependencies corpora. We applied the models trained by de Vries et al. (2022) to the Dagur corpus and continued training these models on Buryat. We analyse the results with respect to language families, script and POS distribution, in three different zero-shot settings: (1) unrelated, (2) related and (3) unrelated+related language. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.
Název v anglickém jazyce
POS Tagging for the Endangered Dagur Language
Popis výsledku anglicky
The application of natural language processing tools opens new ways for the documentation and revitalization of under-resourced languages. In this article we aim to investigate the feasibility of automatic part-of-speech (POS) tagging for Dagur, which is an endangered Mongolic language spoken mainly in northeast China, with no official written standard for all Dagur dialects. We present a new manually annotated corpus for Dagur, which includes about 1,200 tokens, and detail the decisions made during the annotation process. This corpus is used to test transfer of models from other languages, especially from Buryat, which is currently the only Mongolic language included in the Universal Dependencies corpora. We applied the models trained by de Vries et al. (2022) to the Dagur corpus and continued training these models on Buryat. We analyse the results with respect to language families, script and POS distribution, in three different zero-shot settings: (1) unrelated, (2) related and (3) unrelated+related language. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
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OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
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Návaznosti
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Ostatní
Rok uplatnění
2024
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.
ISBN
978-249381410-4
ISSN
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e-ISSN
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Počet stran výsledku
11
Strana od-do
12906-12916
Název nakladatele
European Language Resources Association (ELRA)
Místo vydání
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Místo konání akce
Torino, Italia
Datum konání akce
1. 1. 2025
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
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