Triple
T7388191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goya |
E170434
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | AI inference processor |
C8436
|
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: AI inference processor Context triple: [Goya, instanceOf, AI inference processor]
-
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.
deep learning model
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.
-
C.
hardware accelerator
chosen
A hardware accelerator is a specialized computing device or component designed to perform specific tasks or algorithms more efficiently and faster than a general-purpose processor.
-
D.
neural network API
A neural network API is an interface that allows developers to build, configure, train, and deploy neural network models programmatically without managing low-level implementation details.
-
E.
deep learning framework
A deep learning framework is a software library or platform that provides tools, abstractions, and optimized components to design, train, and deploy neural network models efficiently.
- 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_69c68a5e2c9081909e713ce866e0060a |
completed | March 27, 2026, 1:47 p.m. |
Created at: March 27, 2026, 3:09 p.m.