Triple
T33713088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norwegian counties |
E863794
|
entity |
| Predicate | numberOfUnitsAfterReform |
P204203
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Norwegian counties, numberOfUnitsAfterReform, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUnitsAfterReform Context triple: [Norwegian counties, numberOfUnitsAfterReform, 11]
-
A.
regionAfterReform
Indicates that one region is the successor or resulting region of another after an administrative or political reform.
-
B.
countryAfterReform
Indicates that one country entity represents the state of that country after a specified reform or transformation has taken place.
-
C.
abolishedUnit
Indicates that one administrative or organizational unit has been formally discontinued, dissolved, or eliminated.
-
D.
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.
-
E.
numberAfter2015Reform
Indicates that the associated number reflects values calculated or assigned according to rules or standards implemented after the 2015 reform.
- 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_69f3498844608190bb8f9b14908d2510 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a0346b487088190814e4bd0765cb609 |
completed | May 12, 2026, 3:26 p.m. |
| PD | Predicate disambiguation | batch_6a0346428c60819090e5ea815c0921ca |
completed | May 12, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_6a0346b3b2708190b713ce3dfee1734a |
completed | May 12, 2026, 3:26 p.m. |
Created at: May 1, 2026, 1:43 a.m.