Triple
T19738932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Denmark Region |
E474059
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Løgstør |
—
|
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: Løgstør | Statement: [North Denmark Region, containsCity, Løgstør]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Løgstør Context triple: [North Denmark Region, containsCity, Løgstør]
-
A.
Løgstør
chosen
Løgstør is a small Danish town in northern Jutland known for its historic harbor, maritime heritage, and location along the Limfjord.
-
B.
Ørnskov
Ørnskov is a Danish surname most notably borne by business executive Flemming Ørnskov.
-
C.
Eigtved
Eigtved is a Danish surname most notably associated with Nicolai Eigtved, an 18th-century architect central to the development of Copenhagen’s Rococo architecture.
-
D.
Vækerø
Vækerø is a residential and commercial area in Oslo, Norway, located along the western waterfront and known for its mix of housing, offices, and green spaces.
-
E.
Græsted
Græsted is a small town in North Zealand, Denmark, known for its rural character and location along the Gribskov railway line.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6515f6efc8190a3da113847464399 |
completed | April 20, 2026, 4:16 p.m. |
Created at: April 10, 2026, 1:47 p.m.