Common Data Annotation Challenges and How to Overcome ThemBuilding any reliable machine learning model starts with a question: what is data annotation, and how clean is your labeled data? This post breaks down common annotation challenges and how to fix them using the right workflows, people, and annotation tools. What Edge Cases Look LikeThey vary by task:● Text: Sarcasm, mixed intent, slang● Images: Obstructed objects, rare classes, odd angles● Audio: Background noise, overlapping speakers, accentsAnnotators often guess when edge cases aren’t defined. Clear handling of edge cases during the data annotation process improves both speed and quality. ConclusionMost problems in data annotation come down to three things: unclear guidelines, the wrong tools, or gaps in workflow design.