A BERT Based Approach for Arabic POS Tagging
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10439914" target="_blank" >RIV/00216208:11320/21:10439914 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-85030-2_26" target="_blank" >https://doi.org/10.1007/978-3-030-85030-2_26</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-85030-2_26" target="_blank" >10.1007/978-3-030-85030-2_26</a>
Alternative languages
Result language
angličtina
Original language name
A BERT Based Approach for Arabic POS Tagging
Original language description
Large pre-trained language models, such as BERT, have recently achieved state-of-the-art performance in different natural language processing tasks. However, BERT based models in Arabic language are less abundant than in other languages. This paper aims to design a grammatical tagging system for texts in Arabic language using BERT. The main goal is to label an input sentence with the most likely sequence of tags at the output. We also build a large corpus by combining the available corpora such as the Arabic WordNet and the Quranic Arabic Corpus. The accuracy of the developed system reached 91.69%. Our source code and corpus are available at GitHub upon request.
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
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-030-85029-6
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
311-321
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Madeira
Event date
Jun 16, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000696173400026