English NLP Annotation for LLM Evaluation
Led an annotation initiative for a bilingual Arabic-English dataset aimed at training and evaluating LLMs. Utilized custom Python scripts and Label Studio for efficient labeling workflows, including entity tagging and sentiment analysis. Emphasis was placed on preserving cultural nuances, validating UTF-8/ASCII encodings, and ensuring cross-lingual consistency. Results contributed to enhanced NLP model accuracy in Arabic contexts.