Triple
T17003870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NUTS-1 region NL2 |
E412517
|
entity |
| Predicate | statisticalUnitType |
P40641
|
FINISHED |
| Object | large region |
—
|
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: large region | Statement: [NUTS-1 region NL2, statisticalUnitType, large region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statisticalUnitType Context triple: [NUTS-1 region NL2, statisticalUnitType, large region]
-
A.
statisticalUnitOf
Indicates that one entity serves as the statistical unit (the basic unit of observation or analysis) for which data or statistics are collected or reported about another entity.
-
B.
governmentalUnitType
Indicates the specific category or classification of a governmental unit (such as federal, state, municipal, or other administrative level) that an entity belongs to.
-
C.
statisticalType
chosen
Indicates that one entity specifies the kind or category of statistical characterization or measurement that applies to another entity.
-
D.
spatialUnitType
Indicates the specific kind or category of spatial unit (e.g., parcel, building, region) that characterizes the spatial entity in question.
-
E.
populationUnit
Indicates the unit of measurement in which a population quantity is expressed (e.g., individuals, households, families).
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d380f968819097b59e7bac333ea4 |
completed | April 18, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.