Triple
T22097763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacPherson strut |
E546082
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | automotive suspension design |
C8155
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: automotive suspension design Context triple: [MacPherson strut, instanceOf, automotive suspension design]
-
A.
automotive suspension system
chosen
An automotive suspension system is the integrated assembly of springs, dampers, linkages, and related components that connects a vehicle’s body to its wheels to control ride comfort, handling, and road shock isolation.
-
B.
automobile design
Automobile design is the conceptual and aesthetic process of creating a vehicle’s overall form, function, and user experience, integrating styling, ergonomics, engineering constraints, and brand identity.
-
C.
adaptive suspension system
An adaptive suspension system is a vehicle suspension technology that continuously adjusts damping and stiffness in real time based on driving conditions, road surface, and driver inputs to optimize comfort, handling, and stability.
-
D.
automobile design study
An automobile design study is a conceptual exploration and evaluation of vehicle form, function, and technology to guide the development of future production models.
-
E.
rear-wheel-drive vehicle architecture
A rear-wheel-drive vehicle architecture is a drivetrain layout in which the engine’s power is transmitted primarily to the rear wheels, typically via a driveshaft and rear differential, to provide propulsion and handling characteristics.
- F. None of above.
Provenance (1 batch)
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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
Created at: April 16, 2026, 8:30 p.m.