👉 Annotation math, also known as annotation schema or annotation guidelines, is a structured system used to guide the process of labeling data for machine learning tasks. It involves creating detailed schemas that specify how data should be annotated, including the types of annotations, their relationships, and any specific rules or constraints. This structured approach ensures consistency and accuracy across different annotators, reducing ambiguity and improving the quality of the labeled data. By providing clear instructions, annotation math helps maintain alignment between human annotators and the intended model objectives, ultimately leading to more reliable and effective machine learning models.
