Triple
T3919172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrain-Relative Navigation |
E88916
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | autonomous navigation system |
C14584
|
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 navigation system Context triple: [Terrain-Relative Navigation, instanceOf, autonomous navigation system]
-
A.
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.
-
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.
remotely operated vehicle
A remotely operated vehicle is an unmanned, tethered or wirelessly controlled machine used to perform tasks or gather data in environments that are hazardous, inaccessible, or impractical for direct human presence.
-
D.
advanced driver-assistance system
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.
-
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. chosen
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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.