The Aspect F1 (Aspect Term Extraction F1 Score) is a key evaluation metric for aspect-based sentiment analysis tasks in the field of natural language processing. The Aspect F1 metric evaluates the harmonic mean of precision and recall for correctly identified evaluation aspects in reviews. It is typically reported as a percentage or a score between 0 and 1. This metric is widely used in relevant benchmarks and papers, effectively reflecting model performance in this dimension. Higher values indicate better performance. It helps researchers and engineers quantify the actual performance differences of models in aspect-based sentiment analysis scenarios, facilitating horizontal comparisons across different methods or model versions.