Triple
T4424830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLIP |
E95184
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | vision-language model |
C4177
|
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: vision-language model Context triple: [CLIP, instanceOf, vision-language model]
-
A.
image recognition model
An image recognition model is a computational system that analyzes visual input to automatically identify, classify, and sometimes localize objects, patterns, or features within images.
-
B.
visual modeling language
A visual modeling language is a formal system that uses graphical notations (such as diagrams, symbols, and connectors) to represent, design, and communicate the structure and behavior of complex systems.
-
C.
deep learning model
chosen
A deep learning model is a computational architecture composed of multiple layers of interconnected processing units (neurons) that automatically learn hierarchical representations from data to perform tasks such as classification, prediction, or generation.
-
D.
imager
An imager is a component or system that captures, generates, or processes visual representations of data, scenes, or objects into image form.
-
E.
plate margin network
A plate margin network is the interconnected system of tectonic plate boundaries and their associated geological structures and processes that collectively govern the distribution and interaction of Earth’s lithospheric plates.
- 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_69b3453c2a0c8190926b574c90766db9 |
completed | March 12, 2026, 10:59 p.m. |
Created at: March 12, 2026, 11:30 p.m.