Turkish Data Annotation Services
Native Turkish annotation for NLP, conversational AI, OCR and LLM training. Built for Turkey's booming AI scene — Trendyol, Getir, Peak, and the wave of TR-targeted foundation model projects.
Turkish NLP Has Distinct Challenges
Turkish is agglutinative — single tokens can chain six or seven suffixes (evlerimizden = "from our houses"). Generic English-trained tokenisers fragment Turkish badly, and crowd workers without linguistic training mislabel morpheme boundaries. The result: Turkish models that look fluent on demo but hallucinate on real customer messages.
AI Taggers staffs native Turkish annotators with linguistic training to handle morphological complexity correctly. KVKK-aware workflows for Turkish personal data, plus the Australian-led QA standards we apply globally.
For Turkish-Arabic bilingual work see Arabic annotation. For broader multilingual see native speakers or multilingual.
Turkish Annotation Capabilities
Turkish NER & Sentiment
Named entity recognition tuned for Turkish-specific entities: institutional naming (TC, GLN), business types (Anonim Şirket), and Istanbul/Anatolian regional terms.
Turkish Conversational AI
Intent classification, slot filling, multi-turn dialogue for Trendyol-style e-commerce, Getir-style logistics, and Turkish banking chatbots.
Agglutinative Morphology
Proper handling of Turkish's distinctive suffix chains. Token-level lemmatisation, suffix segmentation, and morphological feature tagging for downstream NLP.
Turkish OCR & Document AI
Government documents, Turkish banking forms, healthcare records. Aware of diacritics (ç, ğ, ı, ö, ş, ü) and historical Ottoman script when needed.
Turkish LLM Training Data
SFT, RLHF, eval data for Turkish foundation models. Native-quality preferences for Turkish-targeted LLMs.
Turkish Speech & Voice
Turkish speech transcription, voice command labeling, Turkish accent variation across Istanbul, Anatolian and diaspora dialects.
Turkish AI Use Cases
From Istanbul fintech to Anatolian agritech.
Test our Turkish annotation
Send 25-50 Turkish records. NER, sentiment, intent, OCR, or LLM training pairs. Free 24-48 hour sample, native-Turkish quality.