Message Understanding Conference Score (MUC) is an important evaluation metric for coreference resolution tasks in the field of natural language processing. MUC calculates recall and precision based on the number of links between coreference chains, focusing on the coverage of links within chains. 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 differences in actual model performance in coreference resolution scenarios, facilitating horizontal comparisons between different methods or model versions.