Self-Directed Data Labeling Project – Text Categorization
Categorized over 200 text snippets into predefined classes by carefully interpreting rubric-based guidelines. Ensured high data integrity through repeated checks and rubric comprehension. Improved throughput and maintained accuracy across multiple text annotation tasks. • Applied sentiment and topical classification to diverse set of texts. • Practiced re-validation of annotations for consistency enhancement. • Leveraged guidelines to resolve ambiguities in label assignment. • Supported AI text classification projects with accurate labeled datasets.