Triple

T15276375
Position Surface form Disambiguated ID Type / Status
Subject Sogn og Fjordane E365150 entity
Predicate containsPart P35 FINISHED
Object Jølster
Jølster is a former municipality in Western Norway known for its scenic lakes and mountains and as the home of painter Nikolai Astrup.
E1167457 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: Jølster | Statement: [Sogn og Fjordane, containsPart, Jølster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jølster
Context triple: [Sogn og Fjordane, containsPart, Jølster]
  • A. Skarø
    Skarø is a small Danish island in the Baltic Sea known for its scenic landscapes, birdlife, and popular summer ice cream and music festival.
  • B. Bjørnø
    Bjørnø is a small Danish island known for its tranquil rural landscape and coastal scenery in the South Funen region.
  • C. Sundbyøster
    Sundbyøster is a district of Copenhagen located on the island of Amager, known primarily as a residential urban area.
  • D. Øksnes
    Øksnes is a coastal municipality in Nordland county, Norway, known for its fishing communities and location within the Vesterålen archipelago.
  • E. Rennesøy
    Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
  • 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: Jølster
Triple: [Sogn og Fjordane, containsPart, Jølster]
Generated description
Jølster is a former municipality in Western Norway known for its scenic lakes and mountains and as the home of painter Nikolai Astrup.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jølster
Target entity description: Jølster is a former municipality in Western Norway known for its scenic lakes and mountains and as the home of painter Nikolai Astrup.
  • A. Skarø
    Skarø is a small Danish island in the Baltic Sea known for its scenic landscapes, birdlife, and popular summer ice cream and music festival.
  • B. Bjørnø
    Bjørnø is a small Danish island known for its tranquil rural landscape and coastal scenery in the South Funen region.
  • C. Sundbyøster
    Sundbyøster is a district of Copenhagen located on the island of Amager, known primarily as a residential urban area.
  • D. Øksnes
    Øksnes is a coastal municipality in Nordland county, Norway, known for its fishing communities and location within the Vesterålen archipelago.
  • E. Rennesøy
    Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00953bc848190b83919f39d5ee37b completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f24967c8190b0bdb84b88a0aaa3 completed May 9, 2026, 4:21 p.m.
NEDg Description generation batch_69ff5fd7068881909a8d85f6bdccedfc completed May 9, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_69ff6073193c8190bb9d1ab18d3d816c completed May 9, 2026, 4:27 p.m.
Created at: April 10, 2026, 3:14 a.m.