Triple
T20053305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ørland Airport |
E499259
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Fosen region |
—
|
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: Fosen region | Statement: [Ørland Airport, serves, Fosen region]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fosen region Context triple: [Ørland Airport, serves, Fosen region]
-
A.
Fosen region
The Fosen region is a coastal area in Trøndelag, Norway, known for its rugged landscapes, fishing communities, and large-scale wind power developments.
-
B.
Vestlandet
Vestlandet is the western region of Norway, known for its dramatic fjords, mountains, and coastal landscapes.
-
C.
Oslofjord region
The Oslofjord region is a coastal area in southeastern Norway centered around the Oslofjord, known for its ports, maritime activities, and proximity to the capital city, Oslo.
-
D.
Lyngen region
The Lyngen region is a scenic area in Troms, northern Norway, known for its dramatic fjords, alpine peaks, and popular outdoor activities like skiing and hiking.
-
E.
Fosen district
chosen
Fosen district is a traditional coastal region in Trøndelag county, Norway, known for its fjords, islands, and rural communities.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6633043a481908359ad232607182a |
completed | April 20, 2026, 5:32 p.m. |
Created at: April 11, 2026, 3:38 p.m.