Triple

T11137449
Position Surface form Disambiguated ID Type / Status
Subject Dornier Do 228 E263450 entity
Predicate maxPassengerCapacity P11680 FINISHED
Object 19 LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 19 | Statement: [Dornier Do 228, maxPassengerCapacity, 19]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: maxPassengerCapacity
Context triple: [Dornier Do 228, maxPassengerCapacity, 19]
  • A. maximumPassengerCapacity chosen
    Indicates the greatest number of passengers that an entity is designed or allowed to carry at one time.
  • B. passengerCapacityCategory
    Indicates the classification of an entity based on the number of passengers it is designed or allowed to carry.
  • C. designedCargoCapacity
    Indicates the maximum amount of cargo an object (such as a vehicle or container) was originally engineered or specified to carry.
  • D. cargoCapacityFeature
    Indicates that an entity has a feature specifying how much cargo it can carry or accommodate.
  • E. aircraftCapacity
    Indicates the maximum number of passengers or amount of load that an aircraft is designed or allowed to carry.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e85f2ea48190bf1ff63af1d7d236 completed April 9, 2026, 5:56 p.m.
PD Predicate disambiguation batch_69d75ce104908190b6cc31ef2f67846a completed April 9, 2026, 8:01 a.m.
Created at: April 8, 2026, 9:28 p.m.