Mukayese: Turkish NLP Strikes Back

Anonymous

Abstract: Having sufficient resources for a language X lifts it from the $\textit{under-resourced}$ languages class, but does not necessarily lift it from the $\textit{under-researched}$ 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. For each benchmark, we work on one or more datasets and present two or more baselines. Moreover, we present four new benchmarking datasets in Turkish for language modeling, sentence segmentation, and spellchecking and correction.