Triple
T32892010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cruise Origin |
E841358
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | autonomous vehicle |
C6073
|
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: autonomous vehicle Context triple: [Cruise Origin, instanceOf, autonomous vehicle]
-
A.
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.
-
B.
autonomous vehicle project
An autonomous vehicle project is an organized effort to design, develop, test, and deploy self-driving systems that enable vehicles to perceive their environment, make driving decisions, and operate safely with minimal or no human intervention.
-
C.
autonomous robotic vehicle
chosen
An autonomous robotic vehicle is a self-navigating mobile machine that perceives its environment, makes decisions, and moves without direct human control.
-
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.
Smart vehicle
A smart vehicle is an automobile equipped with advanced sensors, connectivity, and automated systems that enable it to monitor its environment, assist or automate driving tasks, and communicate with other devices or infrastructure to enhance safety, efficiency, and user experience.
- 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_69f34945ae408190b72d8118c83beb77 |
completed | April 30, 2026, 12:21 p.m. |
Created at: May 1, 2026, 1:18 a.m.