Retrieval and embeddings · Lesson 9 of 16 · 9 min

Spot a missing citation

A citation must connect a claim to source evidence that actually supports it. Merely including a document identifier somewhere in an answer is not adequate grounding.

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learner@clairos:~ $

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-retrieval-embeddings-009.json. Separate the recorded facts from your assumptions.
Hint & worked example
A citation must connect a claim to source evidence that actually supports it. Merely including a document identifier somewhere in an answer is not adequate grounding.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-retrieval-embeddings-009.json
```
Common mistake to avoid: A cited document makes any nearby numeric claim valid.
2
Isolate the deciding signal
Select the claim_supported field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Correct the claim to match the source or withhold it; the citation does not support 60 days.
A successful JSON query isolates claim_supported.
```
jq .claim_supported /opt/ai-lab/cases/aiops-retrieval-embeddings-009.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: correct-unsupported-claim, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-retrieval-embeddings-009-decision.txt.
Hint & worked example
Correct the claim to match the source or withhold it; the citation does not support 60 days.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'correct-unsupported-claim' > /home/learner/lab/aiops-retrieval-embeddings-009-decision.txt
```
Common mistake to avoid: A cited document makes any nearby numeric claim valid.

Understand the pattern

A citation must connect a claim to source evidence that actually supports it. Merely including a document identifier somewhere in an answer is not adequate grounding.

Interpret the evidence

Correct the claim to match the source or withhold it; the citation does not support 60 days.

A tempting mistake

A cited document makes any nearby numeric claim valid.

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-009.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "claim": "refunds allowed for 60 days",
  "source_text": "refunds allowed for 30 days",
  "claim_supported": false
}

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

$ jq .claim_supported /opt/ai-lab/cases/aiops-retrieval-embeddings-009.json

false

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

$ printf '%s\n' 'correct-unsupported-claim' > /home/learner/lab/aiops-retrieval-embeddings-009-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 “correct-unsupported-claim” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Spot a missing citation” justify?Correct the claim to match the source or withhold it; the citation does not support 60 days.A cited document makes any nearby numeric claim valid.Make the change now and gather the missing evidence afterward.

Apply it elsewhere

A colleague concludes: “A cited document makes any nearby numeric claim valid.” What should you do?Accept it because the training command completed.Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Diagnose empty retrieval Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision