تقرير
Mukayese: Turkish NLP Strikes Back
| العنوان: | Mukayese: Turkish NLP Strikes Back |
|---|---|
| المؤلفون: | Safaya, Ali, Kurtuluş, Emirhan, Göktoğan, Arda, Yuret, Deniz |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | 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 Comment: Accepted at Findings of ACL 2022 (Camera Ready) |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2203.01215 |
| رقم الأكسشن: | edsarx.2203.01215 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |