Triple
T16549580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sørreisa |
E402033
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Skøelva
Skøelva is a small village in Troms og Finnmark county in northern Norway, situated within the municipality of Sørreisa.
|
E1229972
|
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: Skøelva | Statement: [Sørreisa, hasSettlement, Skøelva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Skøelva Context triple: [Sørreisa, hasSettlement, Skøelva]
-
A.
Kalvåg
Kalvåg is a coastal fishing village in Bremanger Municipality in Vestland county, Norway, known for its well-preserved wooden waterfront buildings and maritime heritage.
-
B.
Vikersund
Vikersund is a village in Modum municipality in Buskerud, Norway, best known for hosting one of the world’s largest ski flying hills, Vikersundbakken.
-
C.
Strømsø
Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
-
D.
Longva
Longva is a small village in Norway’s Møre og Romsdal county, situated within the municipality of Haram on the island-dotted western coast.
-
E.
Strynø
Strynø is a small Danish island in the Baltic Sea known for its rural charm, traditional village environment, and location between the larger islands of Langeland and Ærø.
- 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: Skøelva Triple: [Sørreisa, hasSettlement, Skøelva]
Generated description
Skøelva is a small village in Troms og Finnmark county in northern Norway, situated within the municipality of Sørreisa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Skøelva Target entity description: Skøelva is a small village in Troms og Finnmark county in northern Norway, situated within the municipality of Sørreisa.
-
A.
Kalvåg
Kalvåg is a coastal fishing village in Bremanger Municipality in Vestland county, Norway, known for its well-preserved wooden waterfront buildings and maritime heritage.
-
B.
Vikersund
Vikersund is a village in Modum municipality in Buskerud, Norway, best known for hosting one of the world’s largest ski flying hills, Vikersundbakken.
-
C.
Strømsø
Strømsø is a historic district and former separate town that now forms part of the city of Drammen in Norway.
-
D.
Longva
Longva is a small village in Norway’s Møre og Romsdal county, situated within the municipality of Haram on the island-dotted western coast.
-
E.
Strynø
Strynø is a small Danish island in the Baltic Sea known for its rural charm, traditional village environment, and location between the larger islands of Langeland and Ærø.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34fc323a88190b5c2a34de0a3c7f0 |
completed | April 18, 2026, 9:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009d2bbe9c81909031d79f93faca6a |
completed | May 10, 2026, 2:58 p.m. |
| NEDg | Description generation | batch_6a009deba8448190a9f480e6807ea6be |
completed | May 10, 2026, 3:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a009e5daf808190ae75d8c3e22aaef2 |
completed | May 10, 2026, 3:03 p.m. |
Created at: April 10, 2026, 5:15 a.m.