Pred F1 (Predicate Identification and Classification F1 Score) is a key evaluation metric for the semantic role labeling task in natural language processing. Pred F1 measures the harmonic mean of precision and recall for predicates that are correctly identified and classified, serving as a foundational metric for semantic role labeling. 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.