Triple
T38604478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truss ministry |
E934304
|
entity |
| Predicate | numberOfDaysInOffice |
—
|
GENERATED |
| Object | 49 |
—
|
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: numberOfDaysInOffice Context triple: [Truss ministry, numberOfDaysInOffice, 49]
-
A.
numberOfTimesInOffice
Indicates the count of separate terms or periods an entity has held a particular office or position.
-
B.
remainedInOfficeAs
Indicates that one entity continued to hold the same official position or role as another entity, without interruption, over a given period.
-
C.
timeInOfficeCharacteristic
Indicates a characteristic or attribute specifically related to the duration or period an entity spends in office or in a particular official role.
-
D.
yearsInPower
Indicates the duration, typically in years, that an entity has held a position of authority or control.
-
E.
timeInNationalGovernment
Indicates the duration that an entity has served within a national-level government.
- F. None of above. chosen
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_69f76ecc17688190b389b693a5927501 |
completed | May 3, 2026, 3:50 p.m. |
Created at: May 3, 2026, 4:32 p.m.