Towards L2-friendly pipelines for learner corpora: A case of written production by L2-Korean learners
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3AV9YIN5BJ" target="_blank" >RIV/00216208:11320/23:V9YIN5BJ - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2023.bea-1.6/" target="_blank" >https://aclanthology.org/2023.bea-1.6/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/2023.bea-1.6" target="_blank" >10.18653/v1/2023.bea-1.6</a>
Alternative languages
Result language
angličtina
Original language name
Towards L2-friendly pipelines for learner corpora: A case of written production by L2-Korean learners
Original language description
"We introduce the Korean-Learner-Morpheme (KLM) corpus, a manually annotated dataset consisting of 129,784 morphemes from second language (L2) learners of Korean, featuring morpheme tokenization and part-of-speech (POS) tagging. We evaluate the performance of four Korean morphological analyzers in tokenization and POS tagging on the L2- Korean corpus. Results highlight the analyzers’ reduced performance on L2 data, indicating the limitation of advanced deep-learning models when dealing with L2-Korean corpora. We further show that fine-tuning one of the models with the KLM corpus improves its accuracy of tokenization and POS tagging on L2-Korean dataset."
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
"Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)"
ISBN
978-1-959429-80-7
ISSN
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e-ISSN
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Number of pages
11
Pages from-to
72-82
Publisher name
Association for Computational Linguistics
Place of publication
Toronto, Canada
Event location
Toronto, Canada
Event date
Jan 1, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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