Triple
T18797042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vendsyssel |
E459660
|
entity |
| Predicate | hasMajorTown |
P316
|
FINISHED |
| Object | Nørresundby |
—
|
NE NERFINISHED |
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: Nørresundby | Statement: [Vendsyssel, hasMajorTown, Nørresundby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nørresundby Context triple: [Vendsyssel, hasMajorTown, Nørresundby]
-
A.
Nørresundby
chosen
Nørresundby is a town in northern Denmark situated across the Limfjord from Aalborg, forming part of the Aalborg metropolitan area.
-
B.
Rødovre
Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
-
C.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
-
D.
Birkerød
Birkerød is a suburban town in northeastern Zealand, Denmark, known for its residential character, green surroundings, and proximity to Copenhagen.
-
E.
Vollebæk
Vollebæk is a Norwegian surname most notably associated with diplomat and former foreign minister Knut Vollebæk.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a020821881909749f6a1c6cd195b |
completed | April 20, 2026, 3:40 a.m. |
Created at: April 10, 2026, 11:53 a.m.