Text Annotation & Content Evaluation (Practice-Based Project)
This project involved structured practice in text annotation and content evaluation tasks aligned with common AI training workflows. The focus was on labeling and categorizing short- and long-form text data based on predefined guidelines. Tasks included text classification, sentiment labeling, and evaluating responses for clarity, relevance, and correctness. I worked with diverse content types including academic explanations, conversational text, and general knowledge prompts. The project emphasized strict adherence to annotation guidelines, consistency across similar data points, and maintaining high accuracy during repetitive tasks. Quality control was maintained through self-review, cross-checking labeled outputs, and ensuring alignment with task instructions. This experience strengthened my ability to interpret context, apply logical reasoning, and maintain precision in structured data labeling environments.