Triple
T17732232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osen |
E442614
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Åfjord |
—
|
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: Åfjord | Statement: [Osen, borderedBy, Åfjord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Åfjord Context triple: [Osen, borderedBy, Åfjord]
-
A.
Åfjord
chosen
Åfjord is a coastal municipality in Trøndelag county, Norway, known for its fjords, fishing, and scenic rural landscapes.
-
B.
Nusfjord
Nusfjord is a historic fishing village in Norway’s Lofoten archipelago, known for its well-preserved wooden rorbuer cabins and scenic coastal setting.
-
C.
Sigerfjord
Sigerfjord is a small coastal village in northern Norway, situated on the island of Hinnøya in the Vesterålen region.
-
D.
Kvæfjord
Kvæfjord is a coastal municipality in Troms og Finnmark county in northern Norway, known for its scenic fjord landscapes and as the birthplace of the traditional cake "Kvæfjordkake."
-
E.
Flekkefjord
Flekkefjord is a coastal town in southern Norway known for its historic wooden architecture, maritime heritage, and picturesque fjord 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e478e7773081909dadb90ff5cb0906 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 10:08 a.m.