Arabic Text Annotation Services
Production-grade Arabic text annotation for NER, sentiment, intent, topics and LLM training. MSA plus Gulf, Levantine, Egyptian, Maghrebi and Iraqi dialects — by native speakers, with Australian-led QA. Trusted by Saudi Arabia, UAE and MENA AI teams.
Arabic Text Annotation, Done Properly
Arabic NLP fails when annotation cuts corners. Machine-translated datasets miss the morphology. Crowdsourced labels miss the dialect. Generalist annotators miss the cultural context that separates a complaint from a compliment in Khaleeji Arabic.
AI Taggers builds Arabic text annotation pipelines that ship to production. Every label comes from a native speaker of the target dialect, working under Australian-led QA with dual annotation and adjudication. Whether you are tuning an Arabic LLM, training a Saudi banking chatbot, or running pan-MENA sentiment analysis — we deliver the linguistic accuracy your model needs.
Looking for the broader Arabic offering? See our Arabic data annotation overview or jump to Arabic NLP datasets for LLM training data.
Arabic Text Annotation Types We Handle
From foundational NLP to LLM alignment — built for Arabic from the ground up.
Named Entity Recognition (NER)
Persons, organisations, locations, dates, monetary values and custom entity types. We handle Arabic-specific entity challenges like definite article (الـ) attachment, transliterated names, and Gulf-region business naming conventions.
Sentiment Analysis
Positive / negative / neutral plus fine-grained aspect-based sentiment. Trained on MENA business contexts: banking reviews, government feedback, e-commerce product opinions, social media reactions across MSA and dialects.
Intent Classification
Conversational AI intent labeling for Arabic chatbots and voice assistants. Multi-turn intent, slot filling, and out-of-scope detection. Optimised for customer support, banking, telecoms and government service bots.
Topic & Category Labeling
Multi-class and multi-label topic classification for content moderation, news categorisation, document routing, and recommendation systems. Hierarchical taxonomies supported.
Relation & Event Extraction
Entity-relation triples, event arguments, temporal expressions. Critical for Arabic knowledge graph construction and structured information extraction from documents and news.
Dialect Identification
Per-sentence dialect tagging (MSA, Gulf, Levantine, Egyptian, Maghrebi, Iraqi) for dialect-aware NLP pipelines and code-switching analysis.
Arabic NLP Use Cases We Power
Arabic LLM Training & RLHF
Instruction-tuning datasets, preference pairs, and red-team prompts for Arabic foundation models. Native-speaker quality is essential for reward modelling.
Saudi Banking & Fintech NLP
Customer query classification, document understanding, fraud signal extraction, Arabic-English transaction descriptions for KSA fintech AI.
Government Service Chatbots
MoI, MoH, MoE, and municipal chatbot training across the GCC. Intent + slot data tuned to formal Arabic and citizen-facing language patterns.
MENA Social Listening
Brand sentiment, crisis detection, influencer identification across Twitter/X, TikTok, Snapchat, and regional platforms. Includes Arabizi normalisation.
Arabic E-commerce Search
Product attribute extraction, query intent, and review sentiment for Noon, Salla, Zid, Jumia and other regional marketplaces.
Arabic OCR Post-Processing
Validation and correction of OCR output for handwritten, historical and printed Arabic documents. Critical for legal, government and archival digitisation.
What Makes Our Arabic Annotation Different
Six quality controls you will not get from crowd-sourced or offshore alternatives.
Arabic Text Annotation FAQ
Do you provide Arabic text annotation software, or only labelled data?▼
What is your accuracy benchmark for Arabic NER and sentiment?▼
Can you handle Arabic social media — Arabizi, code-switching, emoji?▼
How do you handle Arabic morphology in annotation?▼
Do you serve Saudi Arabia and the GCC directly?▼
Free Arabic Text Annotation Sample in 24-48 Hours
Send us 25-50 Arabic records — we'll annotate them for free so you can verify quality before you commit. No sales call required.