Triple
T37200678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AGOVV Apeldoorn |
E922023
|
entity |
| Predicate | hasProfessionalHistory |
—
|
GENERATED |
| Object | yes |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalHistory Context triple: [AGOVV Apeldoorn, hasProfessionalHistory, yes]
-
A.
hasProfessionalCareer
Indicates that an entity engages in or has engaged in a recognized professional occupation or career over a period of time.
-
B.
hasPastOccupation
chosen
Indicates that an entity previously held a particular job, role, or occupation in the past.
-
C.
hasProfessionalSection
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
D.
hasGivenProfession
Indicates that an entity holds or practices a specified profession or occupation.
-
E.
hasProfessionalStatus
Indicates that an entity holds a particular professional standing, rank, or qualification within a field or occupation.
- F. None of above.
Provenance (1 batch)
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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:15 p.m.