Triple

T30521518
Position Surface form Disambiguated ID Type / Status
Subject WorldSSP E776703 entity
Predicate equipmentRegulations P169821 FINISHED
Object homologated production models 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: homologated production models | Statement: [WorldSSP, equipmentRegulations, homologated production models]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: equipmentRegulations
Context triple: [WorldSSP, equipmentRegulations, homologated production models]
  • A. safetyEquipment
    Indicates that one entity serves as safety equipment used to protect another entity from harm or danger.
  • B. hasSafetyRegulationCompliance
    Indicates that an entity adheres to, satisfies, or is in conformity with specified safety regulations or standards.
  • C. equipmentIncludes
    Indicates that one entity contains, comprises, or has as part of its set of items a specified piece or set of equipment.
  • D. protectiveEquipment
    Indicates that one entity serves as protective equipment used to safeguard another entity from harm or risk.
  • E. safetyEquipmentTraditionallyUsed
    Indicates that certain safety equipment has been customarily or historically used in association with a particular entity or activity.
  • F. None of above. chosen

Provenance (4 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_69f2249b23c4819087fa85496d92f43f completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6880b4a788190b7031f48ee4daf3a completed May 2, 2026, 11:26 p.m.
PD Predicate disambiguation batch_69f67e42d6688190b60e91d2c388c555 completed May 2, 2026, 10:44 p.m.
PDg Predicate description generation batch_69f6827a7b9c8190ab13605aacc81df9 completed May 2, 2026, 11:02 p.m.
Created at: April 29, 2026, 8:17 p.m.