Building Foundations for Natural Language Processing of Historical Turkish: Resources and Models

Şaziye Betül Özateş; Tarık Emre Tıraş; Ece Elif Adak; Berat Doğan; Fatih Burak Karagöz; Efe Eren Genç; Esma F. Bilgin Taşdemir

arXiv · 2501.04828

Building Foundations for Natural Language Processing of Historical Turkish: Resources and Models

Şaziye Betül Özateş·Tarık Emre Tıraş·Ece Elif Adak·Berat Doğan·Fatih Burak Karagöz·Efe Eren Genç·Esma F. Bilgin Taşdemir

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Abstract

This paper introduces foundational resources and models for natural language processing (NLP) of historical Turkish, a domain that has remained underexplored in computational linguistics. We present the first named entity recognition (NER) dataset, HisTR, and the first Universal Dependencies treebank, OTA-BOUN, for a historical form of the Turkish language along with transformer-based models trained using these datasets for named entity recognition, dependency parsing, and part-of-speech tagging tasks. Furthermore, we introduce the Ottoman Text Corpus (OTC), a clean corpus of transliterated historical Turkish texts that spans a wide range of historical periods. Our experimental results demonstrate prominent improvements in the computational analysis of historical Turkish, achieving strong performance on tasks that require understanding of historical linguistic structures -- specifically, 90.29% F1 in named entity recognition, 73.79% LAS for dependency parsing, and 94.98% F1 for part-of-speech tagging. They also highlight existing challenges, such as domain adaptation and language variations between time periods. All the resources and models presented are available at https://hf.co/bucolin to serve as a benchmark for future progress in historical Turkish NLP.

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Şaziye Betül Özateş, Tarık Emre Tıraş, Ece Elif Adak, Berat Doğan, Fatih Burak Karagöz, Efe Eren Genç, Esma F. Bilgin Taşdemir. 2025-01-08. Building Foundations for Natural Language Processing of Historical Turkish: Resources and Models. https://arxiv.org/abs/2501.04828

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