Building Foundations for Natural Language Processing of Historical
  Turkish: Resources and Models
Authors: name: Şaziye Betül Özateş, name: Tarık Emre Tıraş, name: Ece Elif Adak, name: Berat Doğan, name: Fatih Burak Karagöz, name: Efe Eren Genç, name: Esma F. Bilgin Taşdemir

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.