Triple
T22411990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ImageNet Classification with Deep Convolutional Neural Networks |
E554013
|
entity |
| Predicate | usesNumberOfGPUs |
P148053
|
FINISHED |
| Object | 2 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
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.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: 2 | Statement: [ImageNet Classification with Deep Convolutional Neural Networks, usesNumberOfGPUs, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNumberOfGPUs Context triple: [ImageNet Classification with Deep Convolutional Neural Networks, usesNumberOfGPUs, 2]
-
A.
gpuType
Indicates the specific kind or model category of GPU associated with an entity.
-
B.
supportsGPUType
Indicates that one entity is compatible with, or capable of operating using, a specified type of GPU.
-
C.
suppliedGPUFor
Indicates that one entity provided or furnished a GPU to another entity for its use or operation.
-
D.
supportsExternalGPU
Indicates that an entity is capable of working with or providing connectivity for an external graphics processing unit (eGPU).
-
E.
GPUPerformanceClaim
Indicates a statement asserting or characterizing the performance capabilities of a GPU, often in terms of speed, efficiency, or comparative advantage.
- F. None of above. chosen
Provenance (4 batches)
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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15943dd84819099e77563da470594 |
completed | April 29, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:46 p.m.