Triple
T20798296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trønderbanen |
E511970
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Værnes |
—
|
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: Værnes | Statement: [Trønderbanen, hasStation, Værnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Værnes Context triple: [Trønderbanen, hasStation, Værnes]
-
A.
Værnes
chosen
Værnes is a village in Trøndelag county, Norway, known for its proximity to Trondheim Airport and its location along the Trondheimsfjord.
-
B.
Våler
Våler is a rural municipality in Innlandet county, Norway, known for its forests, agriculture, and traditional inland Norwegian landscape.
-
C.
Hanevik
Hanevik is a small village in western Norway located within Askøy Municipality in Vestland county.
-
D.
Storvika
Storvika is a small coastal settlement in the Tysfjorden area of Nordland county in northern Norway.
-
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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2ae2c4c819087f620df31dc1aba |
completed | April 21, 2026, 12:19 a.m. |
Created at: April 16, 2026, 12:39 p.m.