Triple
T19840847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Numedal Line |
E476722
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Kongsberg Station |
—
|
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: Kongsberg Station | Statement: [Numedal Line, terminus, Kongsberg Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kongsberg Station Context triple: [Numedal Line, terminus, Kongsberg Station]
-
A.
Kongsberg Station
chosen
Kongsberg Station is a railway station in Kongsberg, Norway, serving as a regional transport hub on the Sørlandet Line.
-
B.
Arendal Station
Arendal Station is the main railway station serving the coastal town of Arendal in Agder county, Norway.
-
C.
Stabekk Station
Stabekk Station is a railway station in Bærum, Norway, serving the Stabekk area on the Drammen Line of the Norwegian rail network.
-
D.
Kjeller
Kjeller is a research-focused village in Lillestrøm, Norway, known as a major hub for defense, aviation, and technology institutions.
-
E.
Kongsberg
Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6580576748190b85e234b01209ae7 |
completed | April 20, 2026, 4:44 p.m. |
Created at: April 10, 2026, 1:51 p.m.