Triple
T33496667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WestEnd City Center |
E857880
|
entity |
| Predicate | hasRetailersType |
P17849
|
FINISHED |
| Object | international 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: international brands | Statement: [WestEnd City Center, hasRetailersType, international brands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRetailersType Context triple: [WestEnd City Center, hasRetailersType, international brands]
-
A.
hasRetailCategory
chosen
Indicates that an entity is associated with a specific retail category or type of retail business.
-
B.
hasRetailProduct
Indicates that an entity offers, sells, or makes available a particular product in a retail context.
-
C.
hasRetailFormat
Indicates that one entity operates or is organized according to a particular retail format or store type.
-
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.
hasRetailUnits
Indicates that one entity possesses, operates, or is associated with one or more retail units (such as stores or outlets).
- 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_69f3497660508190a541826a81f7e9ab |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:38 a.m.