Triple
T38529355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battersea Power Station Estate |
E923316
|
entity |
| Predicate | hasRetailBrandCluster |
—
|
GENERATED |
| Object | international brands |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailBrandCluster Context triple: [Battersea Power Station Estate, hasRetailBrandCluster, international brands]
-
A.
hasRetailBrands
chosen
Indicates that an entity owns, manages, or is associated with one or more retail brands.
-
B.
hasRetailCategory
Indicates that an entity is associated with a specific retail category or type of retail business.
-
C.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
-
D.
hasRetailCharacteristic
Indicates that an entity possesses a specific attribute, feature, or quality relevant to retail contexts (such as pricing, packaging, or point-of-sale properties).
-
E.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
- F. None of above.
Provenance (1 batch)
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_69f76ea8f6348190a5c03fb6292bbee3 |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:32 p.m.