Arg F1 (Argument Identification and Labeling F1 Score) is a key evaluation metric for the Semantic Role Labeling task in Natural Language Processing. Argument F1 measures the proportion of arguments where both the boundary and the role label are correct, reflecting the completeness of semantic role filling. 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 are better.