Triple
T19295278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prada Epicenter New York |
E482545
|
entity |
| Predicate | hasClientExperienceConcept |
P5308
|
FINISHED |
| Object | immersive shopping environment |
—
|
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: immersive shopping environment | Statement: [Prada Epicenter New York, hasClientExperienceConcept, immersive shopping environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClientExperienceConcept Context triple: [Prada Epicenter New York, hasClientExperienceConcept, immersive shopping environment]
-
A.
hasScreenExperience
Indicates that an entity has experience appearing or working on screen, such as in film, television, or digital media productions.
-
B.
hasVirtualExperience
Indicates that one entity possesses or has participated in a virtual or digitally simulated experience related to another entity.
-
C.
hasExperienceElement
Indicates that an experience is composed of, or includes, a specific constituent element or component.
-
D.
providesExperienceOf
Indicates that one entity enables or delivers the experience of another entity to someone or something.
-
E.
hasTypeOfVisitorExperience
chosen
Indicates that an entity is associated with a particular category or kind of visitor experience it provides or involves.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc8533c08190822a917ffa32812d |
completed | April 20, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:31 p.m.