Triple
T6488098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kolsås |
E146564
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Kolsåstoppen
Kolsåstoppen is a prominent hilltop and popular hiking destination in the Kolsås area of Bærum, Norway, known for its scenic views over the surrounding region.
|
E595710
|
NE FINISHED |
How this triple was built (4 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: Kolsåstoppen | Statement: [Kolsås, hasLandmark, Kolsåstoppen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kolsåstoppen Context triple: [Kolsås, hasLandmark, Kolsåstoppen]
-
A.
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.
-
B.
Galdhøpiggen
Galdhøpiggen is the highest mountain in Norway and Scandinavia, located in the Jotunheimen range.
-
C.
Hodnefjell
Hodnefjell is an island that forms part of the Finnøy archipelago in Norway.
-
D.
Slottsfjellet
Slottsfjellet is a historic hill and former fortress site in Tønsberg, Norway, known for its medieval castle ruins and prominent tower overlooking the city.
-
E.
Hovdetoppen
Hovdetoppen is a mountain in Gjøvik, Norway, notable for housing the underground Gjøvik Olympic Cavern Hall built for the 1994 Winter Olympics.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kolsåstoppen Triple: [Kolsås, hasLandmark, Kolsåstoppen]
Generated description
Kolsåstoppen is a prominent hilltop and popular hiking destination in the Kolsås area of Bærum, Norway, known for its scenic views over the surrounding region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kolsåstoppen Target entity description: Kolsåstoppen is a prominent hilltop and popular hiking destination in the Kolsås area of Bærum, Norway, known for its scenic views over the surrounding region.
-
A.
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.
-
B.
Galdhøpiggen
Galdhøpiggen is the highest mountain in Norway and Scandinavia, located in the Jotunheimen range.
-
C.
Hodnefjell
Hodnefjell is an island that forms part of the Finnøy archipelago in Norway.
-
D.
Slottsfjellet
Slottsfjellet is a historic hill and former fortress site in Tønsberg, Norway, known for its medieval castle ruins and prominent tower overlooking the city.
-
E.
Hovdetoppen
Hovdetoppen is a mountain in Gjøvik, Norway, notable for housing the underground Gjøvik Olympic Cavern Hall built for the 1994 Winter Olympics.
- F. None of above. chosen
Provenance (5 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a96a4048190a28dee5fd9258486 |
completed | March 22, 2026, 10:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c653b792f48190b301cdc643db8ddf |
completed | March 27, 2026, 9:53 a.m. |
| NEDg | Description generation | batch_69c6545575788190acb374fcdb7f5edf |
completed | March 27, 2026, 9:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c654c0cdf88190994217223fb2f77a |
completed | March 27, 2026, 9:58 a.m. |
Created at: March 22, 2026, 4:52 p.m.