Triple
T33468251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cantons of France |
E857113
|
entity |
| Predicate | numberAfter2015Reform |
P204087
|
FINISHED |
| Object | about 2054 |
—
|
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: about 2054 | Statement: [cantons of France, numberAfter2015Reform, about 2054]
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Indicates that one entity was substituted or superseded by another as part of a formal reform or restructuring process.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 (4 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a031e24299c81908dcbbf1b88f43dfd |
completed | May 12, 2026, 12:33 p.m. |
| PD | Predicate disambiguation | batch_6a031ce232a48190b62bca3e94162f2f |
completed | May 12, 2026, 12:28 p.m. |
| PDg | Predicate description generation | batch_6a031e231290819086c8869c8039f1f8 |
completed | May 12, 2026, 12:33 p.m. |
Created at: May 1, 2026, 1:37 a.m.