Triple
T23107045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buchanan Galleries |
E576196
|
entity |
| Predicate | hasHealthAndBeautyStores |
P150941
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Buchanan Galleries, hasHealthAndBeautyStores, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthAndBeautyStores Context triple: [Buchanan Galleries, hasHealthAndBeautyStores, true]
-
A.
includesCosmetics
Indicates that one entity contains or encompasses cosmetic products or items as part of its contents or offerings.
-
B.
hasRetailPresenceIn
Indicates that an entity conducts retail operations or maintains a retail outlet, store, or sales presence within a specified location.
-
C.
hasRetailBoutiquesIn
Indicates that an entity operates or maintains retail boutiques located within a specified place or region.
-
D.
hasGroceryStores
Indicates that one entity possesses, contains, or is associated with one or more grocery stores.
-
E.
hasConfectioneryShops
Indicates that an entity operates, contains, or is associated with one or more confectionery shops.
- F. None of above. chosen
Provenance (4 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_69e245f4af548190898d434a64a1e774 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e0bb27c8190a17942d9b88bb158 |
completed | April 29, 2026, 4:50 a.m. |
| PD | Predicate disambiguation | batch_69ef89f020588190b43393e048e7eda3 |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:58 p.m.