Triple
T17547467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aurland–Fagernes road |
E427365
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Fagernes |
—
|
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: Fagernes | Statement: [Aurland–Fagernes road, connects, Fagernes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fagernes Context triple: [Aurland–Fagernes road, connects, Fagernes]
-
A.
Fagernes
chosen
Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
-
B.
Fosnes
Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
-
C.
Fyresdal
Fyresdal is a rural municipality in Telemark county, Norway, known for its forests, lakes, and traditional farming communities.
-
D.
Fjørå
Fjørå is a small Norwegian village situated along the inner reaches of a fjord in Møre og Romsdal county.
-
E.
Vangsnes
Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
- 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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e454626cfc8190a2602ba4934b8e6d |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:49 a.m.