Triple
T16262819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Svellnosbreen |
E394795
|
entity |
| Predicate | hasNearbyMountain |
P651
|
FINISHED |
| Object | Galdhøpiggen |
E92852
|
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: Galdhøpiggen | Statement: [Svellnosbreen, hasNearbyMountain, Galdhøpiggen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Galdhøpiggen Context triple: [Svellnosbreen, hasNearbyMountain, Galdhøpiggen]
-
A.
Galdhøpiggen
chosen
Galdhøpiggen is the highest mountain in Norway and Scandinavia, located in the Jotunheimen range.
-
B.
Saltfjellet
Saltfjellet is a large mountainous region in northern Norway known for its rugged peaks, extensive plateau, and the Saltfjellet–Svartisen National Park.
-
C.
Kolåstinden
Kolåstinden is a prominent alpine peak in Norway’s Sunnmøre Alps, renowned among hikers and ski mountaineers for its steep slopes and panoramic fjord views.
-
D.
Hovdetoppen
Hovdetoppen is a mountain in Gjøvik, Norway, notable for housing the underground Gjøvik Olympic Cavern Hall built for the 1994 Winter Olympics.
-
E.
Hodnefjell
Hodnefjell is an island that forms part of the Finnøy archipelago in Norway.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c5583c8190901e892238cf8dbd |
completed | April 17, 2026, 2:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d9de7548190974851dc54465f0b |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 5:04 a.m.