Triple
T806108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump International Realty |
E17436
|
entity |
| Predicate | usesMarketingChannel |
P18370
|
FINISHED |
| Object | brand association with Trump properties |
—
|
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: brand association with Trump properties | Statement: [Trump International Realty, usesMarketingChannel, brand association with Trump properties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMarketingChannel Context triple: [Trump International Realty, usesMarketingChannel, brand association with Trump properties]
-
A.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
B.
marketingUse
chosen
Indicates that something is used for marketing purposes, such as promotion, advertising, or brand communication.
-
C.
supportsBuyingChannel
Indicates that one entity enables, allows, or is compatible with a particular buying or purchasing channel used by another entity.
-
D.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
E.
mediaMarket
Indicates a relationship where a media outlet or content provider serves, targets, or operates within a particular geographic or demographic market.
- 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.