Triple
T14268293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UltraSPARC T2 |
E353708
|
entity |
| Predicate | floatingPointUnitPerCore |
P91927
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [UltraSPARC T2, floatingPointUnitPerCore, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floatingPointUnitPerCore Context triple: [UltraSPARC T2, floatingPointUnitPerCore, 1]
-
A.
numberOfFloatingPointUnits
chosen
Indicates the quantity of floating-point processing units associated with or contained in an entity.
-
B.
floatingPointRegisterCount
Indicates the number of floating-point registers associated with an entity (such as a processor or execution context).
-
C.
floatingPointUnitSharing
Indicates that two or more processing units share access to a common floating-point execution resource rather than each having a dedicated one.
-
D.
floatingPointPerformance
Indicates the level of computational capability or efficiency an entity has when performing floating-point arithmetic operations.
-
E.
gpuCoreCount
Indicates the number of processing cores present in a GPU.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6358c2288190ac1fd26e688a605d |
completed | April 14, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a7d586c8190846ff242bbf5ac53 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.