Triple
T18016312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MobileNetV2 |
E431005
|
entity |
| Predicate | FLOPs |
P64004
|
FINISHED |
| Object | approximately 300 million multiply-adds (1.0 width, 224x224) |
—
|
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: approximately 300 million multiply-adds (1.0 width, 224x224) | Statement: [MobileNetV2, FLOPs, approximately 300 million multiply-adds (1.0 width, 224x224)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FLOPs Context triple: [MobileNetV2, FLOPs, approximately 300 million multiply-adds (1.0 width, 224x224)]
-
A.
numberOfFloatingPointUnits
Indicates the quantity of floating-point processing units associated with or contained in an entity.
-
B.
floatingPointPerformance
Indicates the level of computational capability or efficiency an entity has when performing floating-point arithmetic operations.
-
C.
FPU
Indicates that one entity functions as or contains a floating-point unit responsible for performing arithmetic operations on non-integer (floating-point) numbers for another entity or within a system.
-
D.
neuralEnginePerformance
Indicates the level or efficiency of processing capability provided by a neural engine in performing AI or machine-learning tasks.
-
E.
computationalCost
chosen
Indicates the amount of computing resources (such as time, memory, or processing power) required to perform a given operation or process.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b523f588819097389e067dda7f23 |
completed | April 19, 2026, 10:57 a.m. |
| PD | Predicate disambiguation | batch_69e3f904b8048190add43883cd7cb191 |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:24 a.m.