Triple
T11888144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Ostrobothnia |
E282843
|
entity |
| Predicate | hasStatisticalRegionCode |
P3446
|
FINISHED |
| Object | NUTS:FI1D5 |
—
|
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: NUTS:FI1D5 | Statement: [Central Ostrobothnia, hasStatisticalRegionCode, NUTS:FI1D5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatisticalRegionCode Context triple: [Central Ostrobothnia, hasStatisticalRegionCode, NUTS:FI1D5]
-
A.
statisticalAreaClassification
Indicates how an area is categorized based on statistical criteria, such as population, density, or other quantitative measures, for analysis or reporting purposes.
-
B.
hasRegionCode
chosen
Indicates that an entity is associated with a specific regional identifier or code.
-
C.
censusRegion
Indicates the broader census-defined geographic region in which an entity (such as a place or population unit) is located or classified.
-
D.
hasProvincialCode
Indicates that an entity is associated with a specific provincial code that identifies its province or administrative region.
-
E.
subregionCodeFor
Indicates that one entity is the code assigned to identify a specific subregion of the other entity.
- F. None of above.
Provenance (3 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a2860c8190a21af5fcddbd2f1e |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.