Triple
T8073491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region Nordjylland |
E188433
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Brønderslev |
E465013
|
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: Brønderslev | Statement: [Region Nordjylland, containsCity, Brønderslev]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brønderslev Context triple: [Region Nordjylland, containsCity, Brønderslev]
-
A.
Brønderslev
chosen
Brønderslev is a town in northern Jutland, Denmark, known as a local commercial and administrative center surrounded by agricultural countryside.
-
B.
Søllerød
Søllerød is a locality in Rudersdal Municipality, north of Copenhagen in eastern Denmark, known for its affluent residential areas and scenic natural surroundings.
-
C.
Skjern
Skjern is a town in western Jutland, Denmark, known for its location near the Skjern River and its surrounding agricultural landscape.
-
D.
Hellebæk
Hellebæk is a coastal town in northeastern Zealand, Denmark, known for its scenic setting near Helsingør and its historic industrial and residential architecture.
-
E.
Næstved
Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
- 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb404a98408190b6c8eecb95ad086d |
completed | March 31, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd6769c6948190805188b09c16bed4 |
completed | April 1, 2026, 6:43 p.m. |
Created at: March 30, 2026, 5:27 p.m.