Triple
T13625170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uber Advanced Technologies Group |
E325559
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | autonomous vehicle research organization |
C15095
|
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 research organization Context triple: [Uber Advanced Technologies Group, instanceOf, autonomous vehicle research organization]
-
A.
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.
-
B.
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.
-
C.
automotive research company
chosen
An automotive research company is an organization that investigates, develops, and evaluates new technologies, designs, and systems to advance vehicle performance, safety, efficiency, and sustainability.
-
D.
autonomous robotic vehicle
An autonomous robotic vehicle is a self-navigating mobile machine that perceives its environment, makes decisions, and moves without direct human control.
-
E.
research and development organization
A research and development organization is an entity dedicated to systematically investigating ideas and technologies to create new knowledge, products, or processes and improve existing ones.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
Created at: April 9, 2026, 9:50 p.m.