The Joint Aspect-Opinion-Sentiment F1 Score is an important evaluation metric for aspect-level sentiment analysis tasks in the field of natural language processing. The joint F1 score requires the aspect, opinion word, and sentiment polarity to be correct simultaneously to count as a match, serving as a comprehensive metric for aspect-level sentiment analysis. 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-level sentiment analysis scenarios, facilitating the comparison of different methods or model versions.