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

arXiv 2501.04828 ↗First posted 8 Jan 2025cs.CLcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 52 references that are in the map. First posted on arXiv 8 Jan 2025.

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19 of 52 references.

References · 19

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  5. 2023The Falcon Series of Open Language Modelscited by 526
  6. 2022UL2: Unifying Language Learning Paradigmscited by 292
  7. 2023ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learningcited by 203
  8. 2021Named Entity Recognition and Classification on Historical Documents: A Surveycited by 47
  9. 2020Parsing as Pretrainingcited by 19
  10. 2024TURNA: A Turkish Encoder-Decoder Language Model for Enhanced Understanding and Generationcited by 13
  11. 2019A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networkscited by 9
  12. 2020Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?cited by 9
7 more
  1. 2020Applying Occam's Razor to Transformer-Based Dependency Parsing: What Works, What Doesn't, and What is Really Necessarycited by 8
  2. 2020Resources for Turkish Dependency Parsing: Introducing the BOUN Treebank and the BoAT Annotation Toolcited by 7
  3. 2023RGAT: A Deeper Look into Syntactic Dependency Information for Coreference Resolutioncited by 3
  4. 2024Dependency Annotation of Ottoman Turkish with Multilingual BERTcited by 3
  5. 2020A Hybrid Approach to Dependency Parsing: Combining Rules and Morphology with Deep Learningcited by 2
  6. 2017Joint POS Tagging and Dependency Parsing with Transition-based Neural Networkscited by 1
  7. 2024A multi-level multi-label text classification dataset of 19th century Ottoman and Russian literary and critical textscited by 1

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