AI Data Evaluation & Annotation Practice (Independent)
Independently evaluated AI-generated responses by assessing accuracy, clarity, relevance, and instruction adherence against structured rubrics. Compared multiple model outputs and ranked responses using the provided guideline criteria, while flagging logical and factual inconsistencies. Performed fact-checking through online research and verification, then applied labeling guidelines to structured text datasets. • Compared model outputs side-by-side to support ranking decisions • Reviewed AI outputs for logical consistency and guideline compliance • Conducted verification using external online research • Applied structured annotation guidelines to text dataset entries