Triple
T15866659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flyvevåbnet |
E384730
|
entity |
| Predicate | headquartersLocation |
P62
|
FINISHED |
| Object | Karup |
E205937
|
NE 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: Karup | Statement: [Flyvevåbnet, headquartersLocation, Karup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karup Context triple: [Flyvevåbnet, headquartersLocation, Karup]
-
A.
Karup
chosen
Karup is a town in central Jutland, Denmark, notable for its major military air base and role as a key Danish defense hub.
-
B.
Knudstrup
Knudstrup is a locality in Denmark, likely a small village or settlement bearing a traditional Danish place name.
-
C.
Knudstrup
Knudstrup is a small locality in present-day Sweden historically notable as the birthplace of the astronomer Tycho Brahe.
-
D.
Knudshoved
Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
-
E.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155603e908190acad1bce2eb6e210 |
completed | April 16, 2026, 9:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa947ba3881909c602f2fc60dd6e8 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.