Triple
T19398031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TACC |
E485243
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | adaptive cruise control system |
C5178
|
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: adaptive cruise control system Context triple: [TACC, instanceOf, adaptive cruise control system]
-
A.
advanced driver-assistance system
chosen
An advanced driver-assistance system is an integrated set of vehicle technologies that monitor the driving environment and vehicle status to assist the driver in controlling the car, enhancing safety, comfort, and efficiency.
-
B.
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.
-
C.
automotive safety system
An automotive safety system is an integrated set of components and technologies designed to prevent accidents or reduce injury and damage when collisions occur.
-
D.
autonomous navigation system
An autonomous navigation system is a self-directed control framework that enables vehicles or robots to perceive their environment, plan routes, and move safely to a destination without human intervention.
-
E.
intelligent transportation system component
An intelligent transportation system component is a hardware or software element that collects, processes, or communicates transportation-related data to optimize traffic flow, enhance safety, and improve overall system efficiency.
- 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
Created at: April 10, 2026, 1:36 p.m.