Triple
T16385270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunnfjord Municipality |
E397904
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Jølster |
E1167457
|
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: Jølster | Statement: [Sunnfjord Municipality, contains, Jølster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jølster Context triple: [Sunnfjord Municipality, contains, Jølster]
-
A.
Jølster
chosen
Jølster is a former municipality in Western Norway known for its scenic lakes and mountains and as the home of painter Nikolai Astrup.
-
B.
Skarø
Skarø is a small Danish island in the Baltic Sea known for its scenic landscapes, birdlife, and popular summer ice cream and music festival.
-
C.
Bjørnø
Bjørnø is a small Danish island known for its tranquil rural landscape and coastal scenery in the South Funen region.
-
D.
Øystese
Øystese is a village in Vestland county, Norway, known for its scenic fjordside setting and role as a local center within the municipality of Kvam.
-
E.
Sundbyøster
Sundbyøster is a district of Copenhagen located on the island of Amager, known primarily as a residential urban area.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e3263c60088190b85a8c02bc3ef315 |
completed | April 18, 2026, 6:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00580fec0c8190b7fb73dbc637fb61 |
completed | May 10, 2026, 10:04 a.m. |
Created at: April 10, 2026, 5:08 a.m.