Five dataset types. One standard of review.

Arabic NLP corpora, bilingual alignment pairs, dialect-segmented training sets, game localization data, and LLM evaluation benchmarks — each built with cultural-context annotation and human validation.

Pick the dataset your pipeline needs

Arabic NLP Corpora

Aligned at the concept, not the token

Dialect-Aware Arabic Corpora

Broad-coverage MSA corpora for classification, NER, and language modeling. Annotated for register, domain, and dialectal contamination. Human-reviewed at the meaning layer.

Dialect-labeled corpora with explicit region tags and code-switching markers. Built for models that must distinguish register and not flatten Arabic into one voice.

Sentence- and segment-level bilingual pairs with cultural equivalence flags. Each pair reviewed by native annotators in both languages before delivery.

Dialogue, UI strings, and lore — reviewed for cultural fit

Evaluation data that surfaces real failure modes

Bilingual game-localization datasets annotated for humor, lore consistency, UI clarity, and culturally sensitive dialogue.

Benchmark datasets designed to expose dialect confusion, cultural-context gaps, and pragmatic reasoning failures beyond token accuracy.

Cultural annotation ships as standard

Every dataset includes dialect metadata, cultural-context annotations, and human-reviewed alignment logs — eliminating unlabeled ambiguity from multilingual pipelines.

Custom dataset builds are available for proprietary terminology, domain-specific evaluation, and pipeline-tailored annotation standards.

Not sure which dataset your pipeline needs?

We help AI and localization teams identify the right bilingual data structure before deployment.