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Mukayese: Turkish NLP Strikes Back

Ali Safaya, Emirhan Kurtuluş, Arda Goktogan, Deniz Yuret


Abstract
Having sufficient resources for language X lifts it from the under-resourced languages class, but not necessarily from the under-researched class. In this paper, we address the problem of the absence of organized benchmarks in the Turkish language. We demonstrate that languages such as Turkish are left behind the state-of-the-art in NLP applications. As a solution, we present Mukayese, a set of NLP benchmarks for the Turkish language that contains several NLP tasks. We work on one or more datasets for each benchmark and present two or more baselines. Moreover, we present four new benchmarking datasets in Turkish for language modeling, sentence segmentation, and spell checking. All datasets and baselines are available under: https://github.com/alisafaya/mukayese
Anthology ID:
2022.findings-acl.69
Volume:
Findings of the Association for Computational Linguistics: ACL 2022
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Smaranda Muresan, Preslav Nakov, Aline Villavicencio
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
846–863
Language:
URL:
https://aclanthology.org/2022.findings-acl.69
DOI:
10.18653/v1/2022.findings-acl.69
Bibkey:
Cite (ACL):
Ali Safaya, Emirhan Kurtuluş, Arda Goktogan, and Deniz Yuret. 2022. Mukayese: Turkish NLP Strikes Back. In Findings of the Association for Computational Linguistics: ACL 2022, pages 846–863, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Mukayese: Turkish NLP Strikes Back (Safaya et al., Findings 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.findings-acl.69.pdf
Video:
 https://aclanthology.org/2022.findings-acl.69.mp4
Code
 alisafaya/mukayese
Data
GLUE