Triple
T24553193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honda Sensing |
E607431
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | driver-assistance technology suite |
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: driver-assistance technology suite Context triple: [Honda Sensing, instanceOf, driver-assistance technology suite]
-
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.
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.
-
C.
driver feature
A driver feature is a specific functionality or characteristic of a driver (software or person) that enables, enhances, or customizes the operation, control, or performance of a vehicle or hardware system.
-
D.
autonomous driving technology
Autonomous driving technology encompasses the hardware, software, and algorithms that enable vehicles to perceive their environment, make driving decisions, and control motion with minimal or no 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
Created at: April 18, 2026, 2:27 a.m.