Triple
T18204677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OPT |
E435873
|
entity |
| Predicate | modelArchitecture |
P48402
|
FINISHED |
| Object | transformer |
—
|
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: transformer | Statement: [OPT, modelArchitecture, transformer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelArchitecture Context triple: [OPT, modelArchitecture, transformer]
-
A.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
B.
modelSize
Indicates the quantitative measure of how large or complex a model is, typically in terms of parameters, layers, or memory footprint.
-
C.
neuralEngineDesigner
Indicates that one entity is the designer or creator of another entity’s neural engine.
-
D.
architectureName
chosen
Indicates the specific name or title assigned to an architecture.
-
E.
graphicsArchitecture
Indicates the underlying design or structural framework that defines how a system’s graphics or visual rendering components are organized and operate.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.