Triple
T35237192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marr Prize |
E1017407
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | computer vision award |
C66323
|
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: computer vision award Context triple: [Marr Prize, instanceOf, computer vision award]
-
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.
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.
-
C.
computer vision research work
A computer vision research work is a scholarly study that develops, analyzes, or evaluates algorithms and systems enabling machines to interpret and understand visual information from images or videos.
-
D.
artificial intelligence competition
An artificial intelligence competition is an organized event where participants develop and pit AI systems against each other to solve defined tasks or challenges under specified rules and evaluation criteria.
-
E.
award of the International Neural Network Society
An award of the International Neural Network Society is a formal recognition conferred by the society to honor outstanding contributions and achievements in the field of neural networks and related areas.
- 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_69f76de235048190b990070c23c51b6b |
completed | May 3, 2026, 3:46 p.m. |
Created at: May 3, 2026, 4:02 p.m.