Case context: A company uses a two-stage pipeline to sort customer support emails. Stage 1 converts the raw message into a structured summary. Stage 2 assigns a priority label. The final labels are often wrong, and you want to trace the problem without using formal error-analysis math.

Question: How should you use an informal pipeline error-analysis method to locate where the mistakes are coming from?

Sample answer: Start by checking the output produced by the first stage before blaming the final classifier. Compare the intermediate summary with the original email and then check the second stage's label on that same example. If the first stage is already wrong, the failure starts there; if the summary is good but the label is wrong, the second stage is the likely source. This step-by-step inspection lets you isolate the component responsible for the bad prediction.

Key points:

• Inspect intermediate results, not only the final label.
• Compare each stage's output against the input or expected behavior.
• Use the comparison to identify which stage introduced the error.

Rubric: The answer must explain that you diagnose the pipeline by examining each stage's output to determine which component introduced the mistake.