Triple
T12207551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | StyleGAN |
E290872
|
entity |
| Predicate | generatorType |
P75139
|
FINISHED |
| Object | style-based generator |
—
|
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: style-based generator | Statement: [StyleGAN, generatorType, style-based generator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generatorType Context triple: [StyleGAN, generatorType, style-based generator]
-
A.
generationMethod
Indicates the process, technique, or procedure by which something is created, produced, or derived.
-
B.
generatorAction
Indicates an action performed by, involving, or affecting a generator within a system or process.
-
C.
hasGeneratorType
chosen
Indicates that an entity is associated with or uses a specific type or category of generator.
-
D.
generationApplicable
Indicates that a particular generation process, method, or rule is valid and can be applied in the given context or situation.
-
E.
generators
Indicates that one entity produces, creates, or brings about another entity or outcome, typically as its source or origin.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.