Triple
T4277603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DistBelief |
E97079
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | distributed deep learning system |
C5494
|
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: distributed deep learning system Context triple: [DistBelief, instanceOf, distributed deep learning system]
-
A.
distributed system
A distributed system is a collection of independent computers that appear to users as a single coherent system by coordinating and communicating over a network to achieve common goals.
-
B.
deep learning framework
chosen
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.
-
C.
deep learning library
A deep learning library is a software framework that provides tools, abstractions, and optimized routines to design, train, and deploy neural network models.
-
D.
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.
-
E.
GPU computing framework
A GPU computing framework is a software platform that enables developers to write, manage, and optimize parallel programs that execute on graphics processing units for high-performance computation.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
Created at: March 12, 2026, 11:07 p.m.