Title
MUKAYESE: Turkish NLP Strikes Back
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 bench-marking datasets in Turkish for language modeling, sentence segmentation, and spell checking. All datasets and baselines are available under: https :// github.com/ alisafaya/mukayese
Year
DOI
Venue
2022
10.18653/v1/2022.findings-acl.69
FINDINGS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2022)
DocType
Volume
Citations 
Conference
Findings of the Association for Computational Linguistics: ACL 2022
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Ali Safaya100.34
Emirhan Kurtuluş200.34
Arda Göktoğan300.34
Deniz Yuret400.34