TL;DR — Data Labeling Platform

Design a data labeling platform that enables teams to annotate training data for machine learning models. The platform supports multiple annotation types (classification, bounding boxes, segmentation, NER, text), manages a distributed workforce of annotators, and implements quality control mechanisms. Key features: Create labeling projects with configurable annotation schemas. Multi-type annotation: classification, bounding box, polygon, NER, text.