Triple
T19382170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hazard Avoidance Cameras |
E484838
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | robotic vision system |
C21609
|
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: robotic vision system Context triple: [Hazard Avoidance Cameras, instanceOf, robotic vision system]
-
A.
robotic sampling system
A robotic sampling system is an automated, programmable mechanism designed to collect, handle, and sometimes analyze physical samples from specified environments with minimal human intervention.
-
B.
robot control system
chosen
A robot control system is a coordinated set of hardware and software components that interpret sensor data, execute decision-making algorithms, and generate actuator commands to direct a robot’s behavior in real time.
-
C.
robotics program
A robotics program is a structured course or initiative that teaches the design, construction, and programming of robots to solve real-world problems or complete specific tasks.
-
D.
computer vision algorithm
A computer vision algorithm is a computational method that processes and interprets visual data from images or videos to automatically extract meaningful information or perform tasks such as detection, recognition, and segmentation.
-
E.
computer vision research laboratory
A computer vision research laboratory is a specialized facility where researchers develop, test, and evaluate algorithms and systems that enable machines to interpret and understand visual information from the world.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
Created at: April 10, 2026, 1:35 p.m.