Triple
T17370999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krødsherad |
E422312
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Norefjell |
—
|
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: Norefjell | Statement: [Krødsherad, hasAttraction, Norefjell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norefjell Context triple: [Krødsherad, hasAttraction, Norefjell]
-
A.
Norefjell
chosen
Norefjell is a prominent Norwegian mountain range and ski resort area known for its alpine terrain and winter sports facilities.
-
B.
Høgefjellet
Høgefjellet is a mountain located on the island of Vågsøy in Vestland county, western Norway.
-
C.
Narvikfjellet
Narvikfjellet is a Norwegian mountain and ski resort near Narvik, known for its scenic fjord views and opportunities for skiing and outdoor recreation.
-
D.
Saltfjellet
Saltfjellet is a large mountainous region in northern Norway known for its rugged peaks, extensive plateau, and the Saltfjellet–Svartisen National Park.
-
E.
Kvitfjell
Kvitfjell is a Norwegian alpine ski resort renowned for hosting major international competitions, including Olympic and World Cup events.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a68ff448190b505861e56df5b6d |
completed | April 19, 2026, 2:14 a.m. |
Created at: April 10, 2026, 5:44 a.m.