Triple
T33468251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cantons of France |
E857113
|
entity |
| Predicate | numberAfter2015Reform |
—
|
GENERATED |
| Object | about 2054 |
—
|
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: numberAfter2015Reform Context triple: [cantons of France, numberAfter2015Reform, about 2054]
-
A.
previousNumberBefore2015Reform
Indicates that an entity had a different (earlier) identifying number prior to a reform or renumbering that took place in 2015.
-
B.
regionAfterReform
Indicates that one region is the successor or resulting region of another after an administrative or political reform.
-
C.
lastReform
Indicates the most recent reform or change that was applied to an entity, typically linking the entity to its latest reform event or version.
-
D.
replacedInReform
Indicates that one entity was substituted or superseded by another as part of a formal reform or restructuring process.
-
E.
afterReformStatus
Indicates the status or condition of an entity following a specified reform or change process.
- 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
Created at: May 1, 2026, 1:37 a.m.