Triple
T15243648
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mo i Rana Airport, Røssvoll |
E364320
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Røssvoll |
E1177941
|
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: Røssvoll | Statement: [Mo i Rana Airport, Røssvoll, locatedIn, Røssvoll]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Røssvoll Context triple: [Mo i Rana Airport, Røssvoll, locatedIn, Røssvoll]
-
A.
Røssvoll
chosen
Røssvoll is a small village in Nordland county, Norway, known for its local airport serving the Rana region.
-
B.
Røyrvik
Røyrvik is a small rural municipality in Trøndelag county, Norway, known for its mountainous landscapes, reindeer herding traditions, and proximity to Børgefjell National Park.
-
C.
Bjerkreim
Bjerkreim is a rural municipality in southwestern Norway known for its rivers, salmon fishing, and agricultural landscape.
-
D.
Røyken
Røyken is a former municipality and suburban area in southeastern Norway, located along the Oslofjord and historically part of Buskerud county.
-
E.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007dcc33081908545ea1a1d2c19fe |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa11f77788190866e0820d33af588 |
completed | May 9, 2026, 9:03 p.m. |
Created at: April 10, 2026, 3:13 a.m.