Triple
T8073522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Region Nordjylland |
E188433
|
entity |
| Predicate | containsGeographicalArea |
P78492
|
FINISHED |
| Object | Vendsyssel |
E459660
|
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: Vendsyssel | Statement: [Region Nordjylland, containsGeographicalArea, Vendsyssel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vendsyssel Context triple: [Region Nordjylland, containsGeographicalArea, Vendsyssel]
-
A.
Vendsyssel
chosen
Vendsyssel is a region in northern Denmark forming the northernmost part of the Jutland peninsula, known for its coastal landscapes and rural towns.
-
B.
Frederikssund
Frederikssund is a Danish town and municipality located on the island of Zealand, known for its Viking heritage and position along the Roskilde Fjord.
-
C.
Abildsø
Abildsø is a residential neighborhood in the borough of Østensjø in Oslo, Norway, known for its green areas and proximity to the lake Østensjøvannet.
-
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.
Djursland
Djursland is a rural peninsula in eastern Jutland, Denmark, known for its varied coastline, beaches, and popular holiday and nature tourism.
- 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_69cc63ecb04881909b1849dc4ef7c2bc |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:27 p.m.