Triple
T12207461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wasserstein GAN |
E290870
|
entity |
| Predicate | domainOfApplication |
P1248
|
FINISHED |
| Object | image generation |
—
|
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: image generation | Statement: [Wasserstein GAN, domainOfApplication, image generation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: domainOfApplication Context triple: [Wasserstein GAN, domainOfApplication, image generation]
-
A.
appliesPrimarilyTo
Indicates that a property, rule, or characteristic is mainly relevant or intended for a particular entity or group, more than for others.
-
B.
appliedPrimarilyTo
Indicates that something is used mainly or chiefly in relation to a particular target, context, or purpose, rather than being used broadly or equally elsewhere.
-
C.
typeOfApplication
Indicates the specific category or kind of application involved in the relationship or action.
-
D.
usedInDomain
chosen
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
-
E.
partOfDomain
Indicates that one entity belongs to, is included within, or is a constituent part of the scope or domain defined by 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_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.