Triple
T18016333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MobileNetV2 |
E431005
|
entity |
| Predicate | hasLayerType |
P16808
|
FINISHED |
| Object | convolutional layers |
—
|
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: convolutional layers | Statement: [MobileNetV2, hasLayerType, convolutional layers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLayerType Context triple: [MobileNetV2, hasLayerType, convolutional layers]
-
A.
hasLayerFunction
Indicates that one entity serves as the functional role or operational purpose of a specific layer within another entity or system.
-
B.
haveType
chosen
Indicates that an entity belongs to or is classified under a specified type or category.
-
C.
isTypicallyLayered
Indicates that something is usually composed of multiple distinct layers arranged one on top of another.
-
D.
hasPackageType
Indicates that an entity is associated with or classified under a particular type or category of package.
-
E.
hasCapType
Indicates that an entity possesses or is characterized by a specific type of cap or cap-like feature.
- 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.