data annotation
The project focused on preparing high-quality AI training data through accurate data labeling, classification, and review. It involved handling thousands of data items while following strict annotation guidelines and resolving edge cases. Quality was ensured through multi-level reviews, low error-rate targets, and adherence to defined accuracy standards.