LAS (Labeled Attachment Score) is an important evaluation metric for syntactic parsing tasks in natural language processing. The labeled attachment score requires both the arc head and the dependency relation type to be correct, making it a comprehensive metric for dependency parsing. It is typically reported as a percentage or a 0–1 score. This metric is widely used in related benchmarks and papers, and it effectively reflects model performance on this dimension. Higher values are better. It helps researchers and engineers quantify differences in actual model performance in syntactic parsing scenarios, making it easier to compare different methods or model versions side by side.