Structured Content Evaluation & Classification (Self-Directed)
This experience involved structured annotation of sample datasets with a focus on text classification and sentiment labeling. I applied labeling guidelines for repeated evaluation and developed skills in error detection and instruction-following, including RLHF concepts. Iterative self-review was essential for accurate decision-based labeling and improving output reliability. • Practiced sentiment analysis, information tagging, and guided evaluations. • Applied annotation rules consistently to maintain labeling quality. • Built familiarity with response ranking and instruction-following for AI training. • Enhanced annotation outcomes through self-driven iterative improvement.