Triple
T32892012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cruise Origin |
E841358
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | self-driving shuttle |
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: self-driving shuttle Context triple: [Cruise Origin, instanceOf, self-driving shuttle]
-
A.
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.
-
B.
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.
-
C.
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.
-
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.
transport technology company
A transport technology company develops and provides innovative digital solutions, platforms, and systems that optimize the planning, operation, and management of transportation services and infrastructure.
- 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.