Triple
T34692272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Tower (Time Warner Center) |
E890930
|
entity |
| Predicate | hasLuxuryBrandTenants |
P94000
|
FINISHED |
| Object | various high-end retailers |
—
|
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: various high-end retailers | Statement: [South Tower (Time Warner Center), hasLuxuryBrandTenants, various high-end retailers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLuxuryBrandTenants Context triple: [South Tower (Time Warner Center), hasLuxuryBrandTenants, various high-end retailers]
-
A.
hasLuxuryBrands
chosen
Indicates that an entity possesses, offers, or is associated with one or more luxury brands.
-
B.
isLuxuryHotel
Indicates that a hotel is classified as a luxury establishment, typically offering high-end amenities, services, and accommodations.
-
C.
hasLeisureTenant
Indicates that an entity has another entity as a tenant specifically for leisure-related use or activities.
-
D.
hasLuxurySuites
Indicates that an entity provides or contains high-end, premium-quality suites as part of its accommodations or offerings.
-
E.
hasLuxuryPositioning
Indicates that an entity is positioned or marketed as a premium, high-end, or luxury offering relative to alternatives.
- 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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7235395488190b246679f9ee8c508 |
completed | May 3, 2026, 10:28 a.m. |
| PD | Predicate disambiguation | batch_69f72157af108190880317a62e634bb0 |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:05 a.m.