Triple
T35959658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summit |
E1039959
|
entity |
| Predicate | energyEfficiencyGFLOPSPerWatt |
P88583
|
FINISHED |
| Object | ~14.7 |
—
|
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: ~14.7 | Statement: [Summit, energyEfficiencyGFLOPSPerWatt, ~14.7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyEfficiencyGFLOPSPerWatt Context triple: [Summit, energyEfficiencyGFLOPSPerWatt, ~14.7]
-
A.
neuralEnginePerformance
Indicates the level or efficiency of processing capability provided by a neural engine in performing AI or machine-learning tasks.
-
B.
powerPerformanceTradeoff
Indicates a relationship where improving performance typically requires increased power consumption, and reducing power use generally leads to lower performance.
-
C.
gpuComputePerformance
Indicates the level of processing capability a GPU can deliver for computational tasks, typically measured in operations per unit time.
-
D.
numberOfFloatingPointUnits
Indicates the quantity of floating-point processing units associated with or contained in an entity.
-
E.
floatingPointPerformance
chosen
Indicates the level of computational capability or efficiency an entity has when performing floating-point arithmetic operations.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b2c771108190adeec151daad5dab |
completed | May 3, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
Created at: May 3, 2026, 4:07 p.m.