NLP Output Evaluator (PhishNet Project)
OtherTextEvaluation Rating
This role focused on assessing the accuracy and reliability of NLP model outputs for a phishing detection system. The tasks included evaluating natural language outputs for sentiment classification and entity extraction. The reviewer ensured the dataset's accuracy and maintained high standards for security-related classifications. • Evaluated NLP outputs for classification and entity extraction reliability
• Assessed sentiment analysis results for accuracy
• Monitored security context in classification results
• Ensured dataset accuracy through thorough validation protocols
This role focused on assessing the accuracy and reliability of NLP model outputs for a phishing detection system. The tasks included evaluating natural language outputs for sentiment classification and entity extraction. The reviewer ensured the dataset's accuracy and maintained high standards for security-related classifications. • Evaluated NLP outputs for classification and entity extraction reliability • Assessed sentiment analysis results for accuracy • Monitored security context in classification results • Ensured dataset accuracy through thorough validation protocols
2025 - 2025