Triple
T36883585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sequoia |
E911546
|
entity |
| Predicate | theoreticalPeakPFLOPS |
P88583
|
FINISHED |
| Object | about 20.1 |
—
|
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: about 20.1 | Statement: [Sequoia, theoreticalPeakPFLOPS, about 20.1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theoreticalPeakPFLOPS Context triple: [Sequoia, theoreticalPeakPFLOPS, about 20.1]
-
A.
numberOfFloatingPointUnits
Indicates the quantity of floating-point processing units associated with or contained in an entity.
-
B.
gpuComputePerformance
Indicates the level of processing capability a GPU can deliver for computational tasks, typically measured in operations per unit time.
-
C.
floatingPointPerformance
chosen
Indicates the level of computational capability or efficiency an entity has when performing floating-point arithmetic operations.
-
D.
maximumOperatingMach
Indicates the highest machine operating level, capacity, or intensity at which the related entity is allowed or designed to function.
-
E.
floatingPointRegisterCount
Indicates the number of floating-point registers associated with an entity (such as a processor or execution context).
- 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_69f76e8335908190b77e7e11d0e80820 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd6b987c8190acae10ec5758a505 |
completed | May 5, 2026, 2:23 p.m. |
| PD | Predicate disambiguation | batch_69f7cf7890008190a8bc355ff2d61c86 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.