Triple
T806071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump National Golf Club |
E17435
|
entity |
| Predicate | hasBrandFeature |
P11989
|
FINISHED |
| Object | Trump name and 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: Trump name and logo | Statement: [Trump National Golf Club, hasBrandFeature, Trump name and logo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandFeature Context triple: [Trump National Golf Club, hasBrandFeature, Trump name and logo]
-
A.
hasBranding
chosen
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
B.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
C.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
D.
hasEventBrand
Indicates that an event is associated with or organized under a particular brand.
-
E.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ace495348190aec66f35ea90bc89 |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa70973c8190adbf08302d1103a9 |
completed | March 1, 2026, 9:06 p.m. |
Created at: March 1, 2026, 7:38 p.m.