A Cross-model Study on Learning Romanian Parts of Speech with Transformer Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A6GQFRL3K" target="_blank" >RIV/00216208:11320/25:6GQFRL3K - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2024.clib-1.1" target="_blank" >https://aclanthology.org/2024.clib-1.1</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
A Cross-model Study on Learning Romanian Parts of Speech with Transformer Models
Original language description
This paper will attempt to determine experimentally if POS tagging of unseen words produces comparable performance, in terms of accuracy, as for words that were rarely seen in the training set (i.e. frequency less than 5), or more frequently seen (i.e. frequency greater than 10). To compare accuracies objectively, we will use the odds ratio statistic and its confidence interval testing to show that odds of being correct on unseen words are close to odds of being correct on rarely seen words. For the training of the POS taggers, we use different Romanian BERT models that are freely available on HuggingFace.
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
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)
ISBN
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ISSN
2367-5578
e-ISSN
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Number of pages
8
Pages from-to
6-13
Publisher name
Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences
Place of publication
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Event location
Sofia, Bulgaria
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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