Senior Reviewer
I worked on a legal-focused data labeling project designed to support AI systems in understanding and processing legal language. The scope of the project involved annotating and categorizing large volumes of legal text, including case summaries, contracts, and statutory excerpts. My primary tasks included text classification (e.g., identifying case type or legal topic), entity recognition (such as parties, jurisdictions, and legal terms), and tagging key elements like claims, defenses, and outcomes. The project required strict adherence to detailed annotation guidelines to ensure consistency and accuracy across the dataset. The project was medium to large in scale, involving thousands of text entries that needed to be reviewed and labeled. Quality measures included regular self-auditing, cross-checking against annotation guidelines, and maintaining a high accuracy threshold. In some cases, I participated in review cycles where labeled data was evaluated for consistency and corrected as needed. Attention to detail and the ability to interpret complex legal language were essential to maintaining data integrity.