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README.md

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-title: README
-emoji: 📚
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-sdk: static
+title: Ottoman Turkish NLP Suite
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+sdk: docker
+app_file: README.md
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-Edit this `README.md` markdown file to author your organization card.
+# Ottoman Turkish NLP Suite 📜🤖
+
+**Bridging the gap between Ottoman Archives and Large Language Models.**
+
+## 🌍 Mission / Misyon
+**Ottoman Turkish NLP Suite** is an open-science initiative dedicated to developing state-of-the-art resources for Low-Resource Historical Languages, with a specific focus on **Ottoman Turkish**.
+
+Despite the vast richness of Ottoman archives, open-source datasets and models capable of handling **Rika (handwritten)** scripts, **Matbu (printed)** texts, and accurate **Transliteration (Arabic to Latin script)** are scarce. This organization aims to fill this gap by providing:
+
+1.  **Curated Datasets:** High-quality instruction-tuning datasets extracted from archives.
+2.  **Fine-Tuned LLMs:** Specialized models (based on Qwen, DeepSeek, Llama) for historical text understanding.
+3.  **OCR/HTR Tools:** Post-processing and recognition tools for digital humanities.
+
+---
+
+**Ottoman Turkish NLP Suite**, Osmanlı Türkçesi ve tarihsel düşük kaynaklı diller için son teknoloji yapay zeka kaynakları geliştirmeyi hedefleyen bir açık bilim inisiyatifidir.
+
+Osmanlı arşivlerinin zenginliğine rağmen, **Rika (el yazısı)**, **Matbu** metinler ve **Transkripsiyon (Arap harflerinden Latin harflerine)** konularında başarılı açık kaynak veri setleri ve modellerin eksikliği büyük bir sorundur. Bu organizasyon, aşağıdaki alanlarda üretim yaparak bu boşluğu doldurmayı amaçlar:
+
+* **Derlenmiş Veri Setleri:** Arşivlerden ve tezlerden çıkarılmış, eğitime hazır veri setleri.
+* **İnce Ayarlı (Fine-Tuned) LLM'ler:** Tarihsel metinleri anlamak için özelleştirilmiş modeller (Qwen, DeepSeek vb.).
+* **OCR/HTR Araçları:** Dijital beşeri bilimler için metin tanıma ve düzeltme araçları.
+
+## 🚀 Key Focus Areas / Odak Alanları
+
+* **Text Transliteration:** Converting Ottoman script (Arabic alphabet) to Modern Turkish (Latin alphabet) with high accuracy.
+* **Historical NER (Named Entity Recognition):** Extracting entities like Place Names, Person Names from 19th and 20th-century texts.
+* **Semantic Search & RAG:** Building Knowledge Graphs and retrieval systems for library archives.
+* **OCR Correction:** Post-processing raw OCR outputs using context-aware LLMs.
+
+## 📚 Featured Datasets / Öne Çıkan Veri Setleri
+
+* **`ottoman-place-names-gazetteer`**: A dataset of 20,000+ unique Ottoman-Turkish place name pairs derived from official state archives. Ideal for vocabulary expansion and transliteration tasks.
+
+## 🛠 Tech Stack
+
+* **Base Models:** Qwen 2.5, DeepSeek-V3, DeepSeek-OCR
+* **Frameworks:** Hugging Face Transformers, Unsloth, vLLM
+* **Domain:** Digital Humanities, Library and Information Science (LIS)
+
+## 👥 Lead Researcher / Araştırmacı
+
+This initiative is led by **Dr. Gökhan Usta** (Istanbul Technical University, Library and Information Science).
+
+* **Website:** [Classifyes](https://classifyes.com)
+* **Institution:** [Istanbul Technical University (ITU)](https://kutuphane.itu.edu.tr)
+
+---
+*For collaborations, please open a discussion in the Community tab.*