Triple
T3499673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DKNY (licensed watches) |
E73933
|
entity |
| Predicate | usesBrandLogo |
P32625
|
FINISHED |
| Object | DKNY logo |
—
|
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: DKNY logo | Statement: [DKNY (licensed watches), usesBrandLogo, DKNY logo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBrandLogo Context triple: [DKNY (licensed watches), usesBrandLogo, DKNY logo]
-
A.
usedBrand
Indicates that an entity has utilized, applied, or operated a particular brand in some context.
-
B.
logoUsedBy
chosen
Indicates that a particular logo is employed or displayed by a specific entity as part of its identity, branding, or representation.
-
C.
logoUsedIn
Indicates that a particular logo is employed or displayed within a specified context, medium, or artifact.
-
D.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
E.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd4eb308190b84e84261ceec229 |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0cd8b0819099da300af09880da |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:18 p.m.