This chapter covers
- Evaluating annotation quality for subjective tasks
- Optimizing annotation quality control with machine learning
- Treating model predictions as annotations
- Combining embeddings/contextual representations with annotations
- Using search and rule-based systems for data annotation
- Bootstrapping models with lightly supervised machine learning
- Expanding datasets with synthetic data, data creation, and data augmentation
- Incorporating annotation information into machine learning models