Triple
T20707389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flytoget airport express train |
E508940
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Stabekk |
—
|
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: Stabekk | Statement: [Flytoget airport express train, terminus, Stabekk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stabekk Context triple: [Flytoget airport express train, terminus, Stabekk]
-
A.
Stabekk
chosen
Stabekk is a suburban area in Bærum, Norway, known for its residential neighborhoods, proximity to Oslo, and good transport connections.
-
B.
Enebakk
Enebakk is a rural municipality in Viken county, Norway, known for its forests, lakes, and proximity to the Oslo metropolitan area.
-
C.
Stangvik
Stangvik was a former municipality in Møre og Romsdal county, Norway, located in the Nordmøre region before being merged into Surnadal.
-
D.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
E.
Steenodde
Steenodde is a small coastal village on the North Sea island of Amrum in Germany, known for its tranquil atmosphere and maritime 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_69e0b4c40ad88190b81f77695366d328 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1917ce08190a54720d4d5b0a02c |
completed | April 21, 2026, 12:15 a.m. |
Created at: April 16, 2026, 12:14 p.m.