Triple
T25971136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | silicon retina |
E645810
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | bio-inspired vision system |
C3399
|
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: bio-inspired vision system Context triple: [silicon retina, instanceOf, bio-inspired vision system]
-
A.
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.
-
B.
bioinspired engineer
A bioinspired engineer is a professional who studies and emulates principles, structures, and processes found in living organisms to design innovative, efficient, and sustainable technologies and systems.
-
C.
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.
-
D.
neuromorphic computing initiative
chosen
A neuromorphic computing initiative is a coordinated effort to research, develop, and deploy hardware and software systems that emulate the structure and function of biological neural networks to achieve more efficient, brain-like computation.
-
E.
behavior-based robotics paradigm
The behavior-based robotics paradigm is an approach to robot control that builds complex, adaptive behavior from the interaction and coordination of many simple, decentralized behavior modules directly coupled to sensors and actuators, rather than relying on centralized symbolic planning.
- 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_69e77e8768648190b27bb578f14bcb88 |
completed | April 21, 2026, 1:41 p.m. |
Created at: April 22, 2026, 8:51 a.m.