Annotations are essential for refining datasets, evaluating model outputs, and improving the quality of AI-generated responses.
Use Case | Annotation Type | Description |
---|---|---|
Sentiment Analysis | Categorical | Label text as Positive, Negative, or Neutral to measure tone |
Factuality Check | Boolean or Text | Validate whether the model output is grounded in the source |
Toxicity Review | Categorical | Flag harmful, biased, or unsafe responses |
Relevance Scoring | Numeric | Rate how well the response addresses the user query |
Grammar/Style Edits | Text | Provide rewritten versions or highlight grammar issues |
Prompt Comparison | Categorical or Numeric | Compare responses from different prompt variants |