Triple
T15276355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sogn og Fjordane |
E365150
|
entity |
| Predicate | containsPart |
P35
|
FINISHED |
| Object | Sunnfjord |
—
|
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: Sunnfjord | Statement: [Sogn og Fjordane, containsPart, Sunnfjord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sunnfjord Context triple: [Sogn og Fjordane, containsPart, Sunnfjord]
-
A.
Sunnfjord
chosen
Sunnfjord is a district in Vestland county in Western Norway, known for its fjords, valleys, and traditional rural communities.
-
B.
Flekkefjord
Flekkefjord is a coastal town in southern Norway known for its historic wooden architecture, maritime heritage, and picturesque fjord setting.
-
C.
Sifjord
Sifjord is a small coastal village in northern Norway, situated on the island of Senja within Troms og Finnmark county.
-
D.
Freifjord
Freifjord is a fjord in western Norway known for its scenic coastal landscape and proximity to historic sites such as Kvernes Church.
-
E.
Nusfjord
Nusfjord is a historic fishing village in Norway’s Lofoten archipelago, known for its well-preserved wooden rorbuer cabins and scenic coastal setting.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00952731c8190bf6a5e6e10c95b94 |
completed | April 15, 2026, 9:55 p.m. |
Created at: April 10, 2026, 3:14 a.m.