Question: In one to three sentences, explain why it is usually more efficient to examine only the wrong predictions in a development set instead of checking every prediction.

Sample answer: If a model is correct on most examples, the wrong predictions are a much smaller set to inspect. For example, if a system gets 97% accuracy on 2,500 items, only 75 items are incorrect, so reviewing those 75 takes far less time than reviewing the 2,425 correct ones.

Key points:

• A small number of errors is much easier to review than the full set.
• Less reviewing time means the analysis is more practical.

Rubric: Full credit requires noting the small error count compared with the much larger number of correct cases and explaining that this reduces review effort.