I Data Review & Text Annotation Project
Reviewed and labeled data based on text used for AI training by applying predefined classification and quality guidelines. Evaluated AI-generated and content written by human for accuracy, relevance, and consistency, and flagged ambiguous or low-quality data. Documented edge cases and followed structured workflows to support model performance, data reliability, and continuous improvement.