Triple
T5943743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gardermoen Line |
E132229
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Gardermoen |
E22608
|
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: Gardermoen | Statement: [Gardermoen Line, passesThrough, Gardermoen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gardermoen Context triple: [Gardermoen Line, passesThrough, Gardermoen]
-
A.
Oslo
Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
-
B.
Trondheim
Trondheim is a historic Norwegian city in Trøndelag county, known for its medieval Nidaros Cathedral and role as a former capital of Norway.
-
C.
Oslo Airport, Gardermoen
chosen
Oslo Airport, Gardermoen is Norway’s main international airport and the primary aviation hub serving the Oslo region.
-
D.
Trondheim Airport, Værnes
Trondheim Airport, Værnes is a major international airport in central Norway serving the city of Trondheim and the surrounding Trøndelag region.
-
E.
Bergens
The Bergens are a race of gloomy, troll-eating creatures who serve as the primary villains in the animated film "Trolls."
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03937b4a88190819a1fd63fc3d3ed |
completed | March 22, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e399f2ec81908e2e38b9fbf8b56a |
completed | March 27, 2026, 1:55 a.m. |
Created at: March 22, 2026, 4:01 p.m.