This study investigates the incongruence between star ratings and written review sentiments within Sri Lankan tourism attraction reviews. Analyzing a dataset of 16,156 reviews from 2010 to 2023, researchers employed a transformer-based pipeline to derive textual sentiment independently of assigned ratings. The analysis reveals that 18.6% of reviews exhibit incongruence, primarily driven by Conservative Rater and Obligatory 5-Star behaviors. These mismatches vary across venue types, with museums demonstrating the highest rates of divergence. Statistical tests, logistic regression, Random Forest, and SHAP analysis identify venue type, reviewer expertise, review length, and temporal factors as key contributors to this phenomenon. The findings demonstrate that star ratings are not interchangeable with textual sentiment and require validation before being used as ground-truth labels in NLP tasks.