Building Foundations for Natural Language Processing of Historical Turkish: Resources and Models - podcast episode cover

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

Jan 11, 2025•27 min•Ep. 367
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Episode description

🤗 Upvotes: 3 | cs.CL

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

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

Arxiv:
http://arxiv.org/abs/2501.04828v1

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. Additionally, we introduce Ottoman Text Corpus (OTC), a clean corpus of transliterated historical Turkish texts that spans a wide range of historical periods. Our experimental results show significant improvements in the computational analysis of historical Turkish, achieving promising results in tasks that require understanding of historical linguistic structures. They also highlight existing challenges, such as domain adaptation and language variations across time periods. All of the presented resources and models are made available at https://huggingface.co/bucolin to serve as a benchmark for future progress in historical Turkish NLP.

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