Triple
T15751088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fauske |
E381845
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Salten district |
E827645
|
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: Salten district | Statement: [Fauske, locatedIn, Salten district]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salten district Context triple: [Fauske, locatedIn, Salten district]
-
A.
Salten district
chosen
Salten district is a traditional region in Nordland county in northern Norway, known for its coastal landscapes, fjords, and the town of Bodø as its main urban center.
-
B.
Voss district
Voss district is a traditional region in western Norway known for its mountainous landscapes, outdoor activities, and strong cultural heritage.
-
C.
Hadeland district
Hadeland district is a traditional rural region in southeastern Norway known for its historic farms, forests, and lakes north of Oslo.
-
D.
Alna district
Alna district is a borough in the eastern part of Oslo, Norway, known for its residential areas, industrial zones, and the Alna River running through it.
-
E.
Bjerke district
Bjerke district is a residential borough in the northeastern part of Oslo, Norway, known for its mix of apartment blocks, green areas, and local commercial centers.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05030e31081908c307a8dc7067db4 |
completed | April 16, 2026, 2:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff876d48588190afec7722cca25633 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.