Which relationships can a generated evidence dataset represent?
A generated dataset can connect audit claims, control requirements and supporting records through explicit relationships, including partial support, contradiction and dependence on other evidence.
A release can include a relationship graph connecting the question under review to the material needed to answer it. Useful entities include review claims, control requirements, business events, records and evidence bundles. The graph describes how those entities relate, rather than treating every attachment as equally supportive.
An expense review claim may depend on both an eligible purchase and an independent approval. A receipt supports the purchase details. An approval record supports authorisation. A role assignment establishes whether the approving role had the required authority. No single document establishes the whole claim.
Generated relationships can express `supports`, `contradicts`, `depends_on` and `covers_part_of`. They can also identify the exact passage or structured field on which a relationship rests. A buyer can ask for reasoning annotations separately from the documents exposed to the model.
This structure supports tasks that require a minimal sufficient bundle, a gap explanation or a defence of a particular inclusion. It also makes partial evidence meaningful: a record can be useful without being enough, and a bundle can support one part of a claim while leaving another unresolved.
Request evidence relationships that make the reasoning structure inspectable beyond the contents of individual documents.
- Audience:
- Model labs
- Content type:
- Explanation
- Buyer question:
- What can be generated
Content release: r-a220eb6e099b243b
Related questions
- What generated artefacts can define the evidence package an agent must produce?
- What can generated material contain beyond approvals and attachments?
- Can a task pack represent evidence that should exist but cannot be found?
- How can generated exports preserve precise evidence references?
- How can generated records represent corrections without erasing earlier evidence?
- How can generated policy and authority records create a useful evidence task?