MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African Languages
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AEEFA87MT" target="_blank" >RIV/00216208:11320/23:EEFA87MT - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173111233&partnerID=40&md5=5c0453f46c2982ca4051784f208b775f" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173111233&partnerID=40&md5=5c0453f46c2982ca4051784f208b775f</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African Languages
Original language description
"In this paper, we present MasakhaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages. We discuss the challenges in annotating POS for these languages using the UD (universal dependencies) guidelines. We conducted extensive POS baseline experiments using conditional random field and several multilingual pretrained language models. We applied various cross-lingual transfer models trained with data available in UD. Evaluating on the MasakhaPOS dataset, we show that choosing the best transfer language(s) in both single-source and multi-source setups greatly improves the POS tagging performance of the target languages, in particular when combined with cross-lingual parameter-efficient fine-tuning methods. Crucially, transferring knowledge from a language that matches the language family and morphosyntactic properties seems more effective for POS tagging in unseen languages. © 2023 Association for Computational Linguistics."
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
"Proc. Annu. Meet. Assoc. Comput Linguist."
ISBN
978-195942972-2
ISSN
0736-587X
e-ISSN
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Number of pages
18
Pages from-to
10883-10900
Publisher name
Association for Computational Linguistics (ACL)
Place of publication
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Event location
Dubrovnik
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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