Triple
T22281644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holbækmotorvejen |
E550745
|
entity |
| Predicate | servesTown |
P847
|
FINISHED |
| Object | Holbæk |
—
|
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: Holbæk | Statement: [Holbækmotorvejen, servesTown, Holbæk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holbæk Context triple: [Holbækmotorvejen, servesTown, Holbæk]
-
A.
Holbæk
chosen
Holbæk is a coastal town and municipality in northwestern Zealand, Denmark, known for its harbor on Holbæk Fjord and role as a regional commercial and cultural center.
-
B.
Vollebæk
Vollebæk is a Norwegian surname most notably associated with diplomat and former foreign minister Knut Vollebæk.
-
C.
Humlebæk
Humlebæk is a coastal town in eastern Denmark known for hosting the renowned Louisiana Museum of Modern Art.
-
D.
Holstebro
Holstebro is a town in western Jutland, Denmark, known as a regional center that hosts significant Danish Army military facilities.
-
E.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
- 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_69e11e44d538819097c6b8f333af3352 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14eac0994819088e39a1b5d39cf18 |
completed | April 29, 2026, 12:19 a.m. |
Created at: April 16, 2026, 8:40 p.m.