AI ReviewPromptingTemplatesPrivilege
Identify Privilege Types
Voir en françaisIdentify Privilege Types
Use this template for repeatable, defensible AI review in Claira.
PromptingTemplate PickerIdentify Privilege Types
When you select this template, Claira displays the prompt configuration panel. Map the output to a review field in your case — typically a Memo field for the privilege determination and type tags.
Privilege TypeMemoclaira-privtype-01
What this prompt is for
This template helps standardize outputs so reviewers can validate and code results quickly.
Step-by-step in Claira
- Open Prompting > Template picker in your case.
- Select Identify Privilege Types and map the output to one or more review fields.
- Run a 10-25 document sample and inspect edge cases first.
- Adjust instructions outside the prompt body (field mapping, workflow settings), then rerun.
The prompt
Analyze this document to determine whether it contains privileged information under Canadian law in the context below:
[insert known solicitors, law firms, clients, or legal matters]
Return ONLY one searchable value:
YESPRIV or NOPRIV.
If YESPRIV, specify all applicable privilege types using searchable tags (e.g., SOLICITORCLIENT, LITIGATION, COMMONINTEREST) and cite key excerpts supporting your determination.Recommended customizations
- Add case context before running (date range, custodians, issue framing).
- Keep output constraints explicit (format, allowed values, fallback behavior).
- Version your template configuration so results remain reproducible.
Worked example
Input excerpt
Email dated 2025-02-14 from Dana Lee to Jordan Park confirms the vendor contract amendment was approved and signed the same day.Expected output shape
A concise answer that follows the exact format required by the prompt and is directly mappable to your selected review field(s).Troubleshooting
- If output is too broad, reduce scope and test with a smaller sample.
- If output format drifts, restate strict formatting requirements in workflow instructions.
- If quality varies across models, compare two models on the same fixed sample set.
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