Triple
T22411981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ImageNet Classification with Deep Convolutional Neural Networks |
E554013
|
entity |
| Predicate | numberOfFullyConnectedLayersInModel |
P148052
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [ImageNet Classification with Deep Convolutional Neural Networks, numberOfFullyConnectedLayersInModel, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFullyConnectedLayersInModel Context triple: [ImageNet Classification with Deep Convolutional Neural Networks, numberOfFullyConnectedLayersInModel, 3]
-
A.
usesFullyConnectedLayersAtEnd
Indicates that the model’s architecture concludes with one or more fully connected (dense) layers applied after preceding layers or modules.
-
B.
hasNumberOfWeightLayers
Indicates the relationship that specifies how many distinct weight layers are present in a given model or structure.
-
C.
numberOfAttentionHeads
Indicates the number of distinct attention heads used within an attention mechanism or layer in a model.
-
D.
numberOfModels
Indicates the quantity or count of models associated with a given entity or context.
-
E.
numberOfConnectedComponents
Indicates the count of distinct, mutually disconnected subgraphs or regions within a given graph or structure.
- F. None of above. chosen
Provenance (4 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_69e11e4e6ce8819085a1e06d886bf21c |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15943dd84819099e77563da470594 |
completed | April 29, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:46 p.m.