Triple
T11380451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple M2 iPad Pro (12.9-inch, 6th generation) |
E269578
|
entity |
| Predicate | graphicsCores |
P11227
|
FINISHED |
| Object | 10-core GPU (Apple M2) |
—
|
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: 10-core GPU (Apple M2) | Statement: [Apple M2 iPad Pro (12.9-inch, 6th generation), graphicsCores, 10-core GPU (Apple M2)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: graphicsCores Context triple: [Apple M2 iPad Pro (12.9-inch, 6th generation), graphicsCores, 10-core GPU (Apple M2)]
-
A.
gpuCoreCount
chosen
Indicates the number of processing cores present in a GPU.
-
B.
performanceCores
Indicates a relationship where certain cores within a processor are designated as high-performance cores optimized for speed and intensive tasks.
-
C.
neuralEngineCores
Indicates the number or configuration of neural engine processing cores associated with a given hardware or system.
-
D.
coreCountCPU
Indicates the number of processing cores that a CPU has.
-
E.
efficiencyCores
Indicates that the related cores are optimized for energy-efficient, low-power processing rather than maximum performance.
- F. None of above.
Provenance (3 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
Created at: April 8, 2026, 9:34 p.m.