Triple
T2239551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Zwirner Gallery |
E49360
|
entity |
| Predicate | hasBusinessOperationType |
P1137
|
FINISHED |
| Object | gallery representation |
—
|
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: gallery representation | Statement: [David Zwirner Gallery, hasBusinessOperationType, gallery representation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinessOperationType Context triple: [David Zwirner Gallery, hasBusinessOperationType, gallery representation]
-
A.
hasOperationType
chosen
Indicates the specific kind or category of operation associated with an entity or process.
-
B.
originalBusinessType
Indicates the initial or primary category of business activity or industry classification associated with an entity before any subsequent changes or reclassifications.
-
C.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
D.
hasActivityType
Indicates the specific kind or category of activity associated with an entity or event.
-
E.
eligibleBusinessType
Indicates that a business entity qualifies under specified criteria to be considered an eligible type for a particular program, rule, or context.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0bb3fac81908b1e8518951dd160 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.