Triple
T17505090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyrøya |
E426292
|
entity |
| Predicate | hasHighestPoint |
P210
|
FINISHED |
| Object |
Løksetinden
Løksetinden is a mountain that forms the highest peak on the island of Dyrøya in Norway.
|
E1272613
|
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: Løksetinden | Statement: [Dyrøya, hasHighestPoint, Løksetinden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Løksetinden Context triple: [Dyrøya, hasHighestPoint, Løksetinden]
-
A.
Hermannsdalstinden
Hermannsdalstinden is a prominent mountain peak in Norway’s Lofoten archipelago, renowned for its dramatic alpine scenery and challenging hiking routes.
-
B.
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.
-
C.
Høgefjellet
Høgefjellet is a mountain located on the island of Vågsøy in Vestland county, western Norway.
-
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.
Tallkrogen
Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
- 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: Løksetinden Triple: [Dyrøya, hasHighestPoint, Løksetinden]
Generated description
Løksetinden is a mountain that forms the highest peak on the island of Dyrøya in Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Løksetinden Target entity description: Løksetinden is a mountain that forms the highest peak on the island of Dyrøya in Norway.
-
A.
Hermannsdalstinden
Hermannsdalstinden is a prominent mountain peak in Norway’s Lofoten archipelago, renowned for its dramatic alpine scenery and challenging hiking routes.
-
B.
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.
-
C.
Høgefjellet
Høgefjellet is a mountain located on the island of Vågsøy in Vestland county, western Norway.
-
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.
Tallkrogen
Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45214d44c8190b1bf04bf24ab8e81 |
completed | April 19, 2026, 3:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01c20a6370819098b4876ca8ff1ebf |
completed | May 11, 2026, 11:48 a.m. |
| NEDg | Description generation | batch_6a01c3881f6081908f13c4033933b252 |
completed | May 11, 2026, 11:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01c41859008190b786bdc2c09f24d1 |
completed | May 11, 2026, 11:57 a.m. |
Created at: April 10, 2026, 5:48 a.m.