Triple
T14028572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sør-Fron |
E337527
|
entity |
| Predicate | locatedInFormerCounty |
P29444
|
FINISHED |
| Object | Oppland county |
—
|
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: Oppland county | Statement: [Sør-Fron, locatedInFormerCounty, Oppland county]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oppland county Context triple: [Sør-Fron, locatedInFormerCounty, Oppland county]
-
A.
Oppland
chosen
Oppland is a former inland county in southeastern Norway known for its mountainous terrain, national parks, and popular skiing and hiking areas.
-
B.
Trøndelag County
Trøndelag County is a large region in central Norway known for its historic city of Trondheim, coastal and fjord landscapes, and role as a cultural and economic hub of the country.
-
C.
Nordland county
Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
-
D.
Akershus county
Akershus county was a former county in southeastern Norway that historically surrounded Oslo and included both urban suburbs and rural areas before being merged into Viken county.
-
E.
Hedmark
Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa830ac81908cb7df7c9e81e42a |
completed | April 14, 2026, 12:14 p.m. |
Created at: April 9, 2026, 10:20 p.m.