Triple
T36976348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyde Park, Sandton |
E914708
|
entity |
| Predicate | hasRetailProfile |
P88487
|
FINISHED |
| Object | luxury brands |
—
|
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 brands | Statement: [Hyde Park, Sandton, hasRetailProfile, luxury brands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailProfile Context triple: [Hyde Park, Sandton, hasRetailProfile, luxury brands]
-
A.
hasRetailCharacteristic
chosen
Indicates that an entity possesses a specific attribute, feature, or quality relevant to retail contexts (such as pricing, packaging, or point-of-sale properties).
-
B.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
C.
hasRetailNetwork
Indicates that an entity operates or is associated with a system of retail outlets or distribution channels through which products or services are sold.
-
D.
hasRetailProduct
Indicates that an entity offers, sells, or makes available a particular product in a retail context.
-
E.
hasRetailCategory
Indicates that an entity is associated with a specific retail category or type of retail business.
- 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_69f76e8d13b4819089af24a47ce092fc |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:14 p.m.