Triple
T29589267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French territorial reform of 2014 |
E754107
|
entity |
| Predicate | changedNumberOfRegionsBefore |
P167486
|
FINISHED |
| Object | 22 |
—
|
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: 22 | Statement: [French territorial reform of 2014, changedNumberOfRegionsBefore, 22]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: changedNumberOfRegionsBefore Context triple: [French territorial reform of 2014, changedNumberOfRegionsBefore, 22]
-
A.
numberOfNewRegions
Indicates the count of regions that have been newly created or added within a specified context or time frame.
-
B.
previouslyContainedRegion
Indicates that one region used to spatially contain another region at some earlier time, but does not necessarily do so now.
-
C.
changedNumberOf
Indicates that the quantity of one entity has been altered by another entity or event.
-
D.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
E.
reorganisedRegion
Indicates that a region has undergone a structural or administrative change, resulting in a new or altered regional configuration.
- 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66db2924881909d004d77dcfd26e7 |
completed | May 2, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
| PDg | Predicate description generation | batch_69f6691da93081909deaf680614fc900 |
completed | May 2, 2026, 9:14 p.m. |
Created at: April 28, 2026, 6:13 p.m.