NLP Data Labeling for Transport Services
Categorized and labeled thousands of user queries and feedback entries to train Uber's customer support Chatbots. Identified key entities such as locations, timestamps, and issue types using NER. Focused on nuances in language to improve sentiment analysis accuracy. Contributed to a project that scaled to 100,000+ labeled data points with rigorous cross-verification to ensure model reliability.