Triple
T15302617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kvinnherad |
E365824
|
entity |
| Predicate | locatedOn |
P40
|
FINISHED |
| Object | Varaldsøy |
E1198398
|
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: Varaldsøy | Statement: [Kvinnherad, locatedOn, Varaldsøy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varaldsøy Context triple: [Kvinnherad, locatedOn, Varaldsøy]
-
A.
Varaldsøy
chosen
Varaldsøy is a large island in Vestland county, Norway, known for its scenic fjord landscape and rural communities within the municipality of Kvinnherad.
-
B.
Rolvsøy
Rolvsøy is a district and former municipality that now forms part of the city of Fredrikstad in Viken county, Norway.
-
C.
Dillingøy
Dillingøy is an island located in southeastern Norway, within the coastal area of Moss in Østfold/Viken county.
-
D.
Lauvøy
Lauvøy is an island that forms part of the Finnøy area in Norway, known for its coastal landscape and maritime surroundings.
-
E.
Vågsøy
Vågsøy is a coastal island and former municipality in Vestland county, western Norway, known for its rugged North Sea coastline, lighthouses, and fishing communities.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ccd575c8190aa43262d3b73ef3c |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fffee31b70819092d0583100a7101a |
completed | May 10, 2026, 3:43 a.m. |
Created at: April 10, 2026, 3:15 a.m.