ACL2022

Mukayese: Turkish NLP Strikes Back

Ali Safaya, Emirhan Kurtulus, Arda Göktogan, Deniz Yüret

30 citations

Abstract

Having sufficient resources for language X lifts it from the under-resourced languages class, but not necessarily from the underresearched 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 Related Work In this section, we discuss efforts similar to ours. We give an overview of efforts on building multilingual benchmarks, and we mention some of the monolingual benchmarks as well.