Triple
T17614148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kvinnherad Municipality |
E429039
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Husnes |
—
|
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: Husnes | Statement: [Kvinnherad Municipality, contains, Husnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Husnes Context triple: [Kvinnherad Municipality, contains, Husnes]
-
A.
Husnes
chosen
Husnes is a village and commercial center in Kvinnherad municipality in Vestland county, Norway.
-
B.
Hestnes
Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
-
C.
Frekhaug
Frekhaug is a village in western Norway that serves as a local residential and service center within Alver Municipality in Vestland county.
-
D.
Vangsnes
Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
-
E.
Namdalseid
Namdalseid is a former rural municipality in Trøndelag county, Norway, known for its forests, agriculture, and coastal landscape along the Namsenfjorden.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d2fd96481908c9f3b566fca6907 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 5:51 a.m.