Triple
T24988823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curator at Museum Folkwang |
E625392
|
entity |
| Predicate | employedInSector |
P62538
|
FINISHED |
| Object | museum sector |
—
|
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: museum sector | Statement: [Curator at Museum Folkwang, employedInSector, museum sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employedInSector Context triple: [Curator at Museum Folkwang, employedInSector, museum sector]
-
A.
hasOccupationSector
chosen
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
B.
employedTo
Indicates that one entity is hired or engaged to perform work, services, or duties for another entity.
-
C.
employmentBasedCategory
Indicates that one entity’s classification or status is determined by its relationship to employment, such as being based on a specific job, role, or work-related category.
-
D.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
E.
employedUnder
Indicates that one entity works as an employee under the authority, supervision, or organizational structure of another entity.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 6:03 a.m.