Triple
T14056514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tårnby Municipality |
E338233
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Kastrup |
E343798
|
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: Kastrup | Statement: [Tårnby Municipality, hasTown, Kastrup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kastrup Context triple: [Tårnby Municipality, hasTown, Kastrup]
-
A.
Kastrup
chosen
Kastrup is a district in the Tårnby Municipality near Copenhagen, Denmark, best known for hosting the country’s main international airport.
-
B.
Glostrup
Glostrup is a suburban town and municipality in the Copenhagen metropolitan area of Denmark, known for its residential neighborhoods and commercial districts.
-
C.
Hellerup
Hellerup is a suburban district just north of central Copenhagen, known for its affluent residential areas, seaside location, and role as a key transport and commercial hub.
-
D.
Emdrup
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
-
E.
Hornbæk
Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8e6d008190af8892f34c5cefbd |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c255d8c81908bdac0a28718563e |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 9, 2026, 10:20 p.m.