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Mukayese: Turkish NLP Strikes Back

About

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

Ali Safaya, Emirhan Kurtulu\c{s}, Arda G\"okto\u{g}an, Deniz Yuret• 2022

Related benchmarks

TaskDatasetResultRank
Machine Reading ComprehensionBELEBELE Target Language
MRC Score28.11
24
Causal ReasoningXCOPA
XCOPA Causal Reasoning Score64.2
8
Cross-lingual Question AnsweringEXAMS TR
Score30.03
8
News Category ClassificationNews Category Classification
Score66.8
8
Natural Language InferenceMNLI TR
Score33.4
8
Irony DetectionIronyTR
Score50
8
Semantic Textual SimilaritySTSb-TR
STSb Score12.91
8
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