Triple
T824286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trump International Hotel & Tower |
E17818
|
entity |
| Predicate | brandCategory |
P87
|
FINISHED |
| Object | luxury hotel |
—
|
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: luxury hotel | Statement: [Trump International Hotel & Tower, brandCategory, luxury hotel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandCategory Context triple: [Trump International Hotel & Tower, brandCategory, luxury hotel]
-
A.
brandSegment
Indicates the specific market segment or customer group that a brand is targeted toward or associated with.
-
B.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
C.
brandFocus
Indicates that a brand primarily concentrates its efforts, messaging, or resources on a particular target, theme, or market segment.
-
D.
brand
Indicates that one entity is the commercial brand or label under which another entity (such as a product, service, or organization) is marketed or identified.
-
E.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab7d3984819089aefbf12d3b3c2c |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa781e1081909df006f730296c53 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.