What should I specify when requesting a mismatch dataset?
A checklist of the decisions a buyer should state when requesting generated mismatch material, from domain and root cause taxonomy to output form and evaluation split.
State these decisions in your request, and generation can be shaped around them rather than guessed.
- The domain and the pair of systems that disagree, such as ledger against bank feed or claim against payment. - The root cause taxonomy you want covered, and any causes you want over- or under-represented. - The policy set: tolerances, approval limits, reason codes and escalation rules that decide the correct action. - Difficulty controls: how many decoys, how many missing links, and how ambiguous the evidence may be. - Expected outcome types, including wait, escalate and no action alongside correction. - The output form: records only, task statements, step-by-step trajectories, or an interactive environment. - A rule for which templates or scenario families are held back for evaluation only. - Format, identifier style and the schema version your pipeline will ingest.
A request that names its taxonomy, policies, difficulty controls and splits is far easier to generate, inspect and compare across rounds.
- Audience:
- Model labs
- Content type:
- Checklist
- Buyer question:
- What can be generated
Content release: r-a220eb6e099b243b
Related questions
- What would a generated freight invoice versus proof-of-delivery task contain?
- What file layout and schema would a generated case set use?
- Can a pack include policies, tolerances and escalation rules, not just records?
- Which record elements should a dataset for this workflow include?
- What records and relationships can MirrorFirm generate for this workflow?
- What fields and file formats can a generated mismatch pack use?