Triple
T1180422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | deep feedforward networks |
E25122
|
entity |
| Predicate | canUseOptimizer |
P9928
|
FINISHED |
| Object | SGD |
—
|
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: SGD | Statement: [deep feedforward networks, canUseOptimizer, SGD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canUseOptimizer Context triple: [deep feedforward networks, canUseOptimizer, SGD]
-
A.
canUse
chosen
Indicates that one entity has the ability, permission, or suitability to make use of another entity or resource.
-
B.
canBeImplementedWith
Indicates that one entity is capable of being realized, executed, or fulfilled through the use or application of another entity.
-
C.
usesOpticsType
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
D.
canBeAugmentedWith
Indicates that one entity is capable of being enhanced, expanded, or supplemented by another entity.
-
E.
supportsUse
Indicates that one entity enables, allows, or is compatible with the use or operation of another entity.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd32c5f48190b4e2d39fa052cbb7 |
completed | March 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69a4bb59ca6c81908597a81646674aaa |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.