Triple
T13410495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fugaku |
E320072
|
entity |
| Predicate | additionalAssistantCoresPerCPU |
P109797
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Fugaku, additionalAssistantCoresPerCPU, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: additionalAssistantCoresPerCPU Context triple: [Fugaku, additionalAssistantCoresPerCPU, 4]
-
A.
efficiencyCores
Indicates that the related cores are optimized for energy-efficient, low-power processing rather than maximum performance.
-
B.
bigCoreCount
Indicates that an entity (such as a processor or system) has a relatively large number of cores compared to a typical or baseline configuration.
-
C.
neuralEngineCores
Indicates the number or configuration of neural engine processing cores associated with a given hardware or system.
-
D.
gpuCoreCount
Indicates the number of processing cores present in a GPU.
-
E.
hasCPUCore
Indicates that an entity (typically a computing device or processor) possesses or includes a specific CPU core as one of its components.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb3facc819088c1af3b59237e7a |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:35 p.m.