Triple
T21537626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Versailles |
E531389
|
entity |
| Predicate | hasEnclosedMall |
P16039
|
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: [Place Versailles, hasEnclosedMall, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnclosedMall Context triple: [Place Versailles, hasEnclosedMall, true]
-
A.
hasShoppingMall
chosen
Indicates that one entity possesses, contains, or includes a shopping mall within its area or domain.
-
B.
hasShoppingMallName
Indicates that an entity (such as a shopping mall) is associated with or identified by a specific name.
-
C.
isOneOfLargestMallsIn
Indicates that a mall ranks among the largest shopping centers located within a specified area or region.
-
D.
isOutdoorMall
Indicates that a shopping area is an open-air mall, where stores are arranged outdoors rather than within an enclosed building.
-
E.
isOneOfLargestOutletMallsIn
Indicates that an outlet mall ranks among the largest within a specified geographic area or region.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0fdf448190b47ac7c28904f86b |
completed | April 26, 2026, 11:17 p.m. |
| PD | Predicate disambiguation | batch_69e6320766308190ba5dca2f7c826aa4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:27 p.m.