AI/data labeling support via guideline-based annotation (text classification, entity recognition, sentiment analysis)
TextWorked with annotation guidelines to support machine learning training through text classification and entity recognition tasks. Focused on producing precise ground-truth labels for downstream AI model improvement, with attention to data accuracy and quality control. Performed quality assurance by flagging potential errors and inconsistencies in the annotated outputs.• Entity recognition labeling aligned to NER-focused annotation requirements • Text classification and sentiment analysis related labeling • Error detection and quality checks to ensure data integrity • Consistent adherence to complex labeling guidelines
2024 - Present