Retrieval and embeddings · Lesson 7 of 16 · 7 min

Review retrieval results

Retrieval results should be judged for relevance, coverage and source quality. A ranking position is not a guarantee that a passage supports the answer.

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-retrieval-embeddings-007.json. Separate the recorded facts from your assumptions.
Hint & worked example
Retrieval results should be judged for relevance, coverage and source quality. A ranking position is not a guarantee that a passage supports the answer.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-retrieval-embeddings-007.json
```
Common mistake to avoid: The first result is always sufficient evidence.
2
Isolate the deciding signal
Select the supports_query field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Reject or flag the top result because it does not support the refund question.
A successful JSON query isolates supports_query.
```
jq .supports_query /opt/ai-lab/cases/aiops-retrieval-embeddings-007.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: reject-irrelevant-passage, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-retrieval-embeddings-007-decision.txt.
Hint & worked example
Reject or flag the top result because it does not support the refund question.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'reject-irrelevant-passage' > /home/learner/lab/aiops-retrieval-embeddings-007-decision.txt
```
Common mistake to avoid: The first result is always sufficient evidence.

Understand the pattern

Retrieval results should be judged for relevance, coverage and source quality. A ranking position is not a guarantee that a passage supports the answer.

Interpret the evidence

Reject or flag the top result because it does not support the refund question.

A tempting mistake

The first result is always sufficient evidence.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-retrieval-embeddings-007.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "rank": 1,
  "query": "refund deadline",
  "passage_topic": "shipping time",
  "supports_query": false
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .supports_query /opt/ai-lab/cases/aiops-retrieval-embeddings-007.json

false

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'reject-irrelevant-passage' > /home/learner/lab/aiops-retrieval-embeddings-007-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “reject-irrelevant-passage” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Review retrieval results” justify?The first result is always sufficient evidence.Make the change now and gather the missing evidence afterward.Reject or flag the top result because it does not support the refund question.

Apply it elsewhere

A colleague concludes: “The first result is always sufficient evidence.” What should you do?Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Compare similarity scores Try an incident drill

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Case methodology: evidence, limits, decision