Triple
T806096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump International Realty |
E17436
|
entity |
| Predicate | targetsMarketSegment |
P16877
|
FINISHED |
| Object | affluent buyers |
—
|
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: affluent buyers | Statement: [Trump International Realty, targetsMarketSegment, affluent buyers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetsMarketSegment Context triple: [Trump International Realty, targetsMarketSegment, affluent buyers]
-
A.
targetMarket
Indicates the group of consumers or organizations that a product, service, or campaign is specifically intended and designed to reach.
-
B.
brandSegment
chosen
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
-
C.
targetsGroup
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
D.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
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.