{
  "title": "Restaurant prep videos for AI task and action recognition",
  "source_page": "https://fiund.com/industries/restaurant-prep-data",
  "authorship": "Original fictional Fiund editorial exercise. No actual operating records or third-party source assets are included.",
  "example": {
    "title": "Check a practice assembly against the revised ticket",
    "context": "Reusable inert training pieces represent a cold-station task. The target is the correspondence between ticket, visible selection and result, with no real recipe or live cooking.",
    "records": [
      [
        "ORDER-P1",
        "Original practice ticket",
        "Use bowl Blue and training pieces A, B and C."
      ],
      [
        "ORDER-P2",
        "Confirmed revised ticket",
        "Replace C with D for the same practice order. Bowl Blue and pieces A and B remain unchanged."
      ],
      [
        "TAKE-P3",
        "Observed demonstration",
        "The take shows Blue with A, B and C, followed by a correction in which C leaves view. The endpoint does not show D."
      ],
      [
        "NOTE-P4",
        "Operator intention",
        "A note says the operator intended to complete the revised order, without a final check."
      ]
    ],
    "question": "Does the supplied evidence verify the result requested by P2? Describe the observed correction and its remaining gap.",
    "answer": "P2 requires Blue with A, B and D. P3 supports an initial old-version assembly and the visible removal of C, but it does not show D in the endpoint. P4 records intent and cannot establish the final state. The revised result remains unverified. Request a matching final view or independent check, rather than label the intended sequence as completed.",
    "failureModes": [
      "Treating the removal of the old piece as proof that the replacement was added.",
      "Using the original ticket or an intention note to override missing final evidence."
    ],
    "fields": [
      [
        "Order revision",
        "Identify the changed requirement before judging the take."
      ],
      [
        "Action interval",
        "Locate the initial assembly and correction separately."
      ],
      [
        "Observed endpoint",
        "Record the evidence for the final state and unresolved visibility."
      ]
    ],
    "holdout": "Use a different vessel and piece-label style with a clear revised endpoint. Test whether the model follows the new ticket rather than the original prop layout.",
    "boundary": "Use harmless training materials away from active hazards. Exclude customers, live tickets, payment screens, proprietary recipes and staff schedules."
  }
}