Triple

T15276381
Position Surface form Disambiguated ID Type / Status
Subject Sogn og Fjordane E365150 entity
Predicate containsPart P35 FINISHED
Object Fjaler
Fjaler is a small municipality in Western Norway known for its fjord landscapes and rural communities.
E1148836 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: Fjaler | Statement: [Sogn og Fjordane, containsPart, Fjaler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fjaler
Context triple: [Sogn og Fjordane, containsPart, Fjaler]
  • A. Fjell
    Fjell was a former municipality in Vestland county, Norway, encompassing coastal and island communities west of Bergen.
  • B. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • C. Lifjell
    Lifjell is a mountainous plateau and popular outdoor recreation area in Telemark, Norway, known for its hiking, skiing, and scenic alpine landscapes.
  • D. Follebu
    Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
  • E. Flørli
    Flørli is a small, roadless village in Norway’s Lysefjord best known for its historic hydropower station and one of the world’s longest wooden stairways, with 4,444 steps climbing the mountainside.
  • 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: Fjaler
Triple: [Sogn og Fjordane, containsPart, Fjaler]
Generated description
Fjaler is a small municipality in Western Norway known for its fjord landscapes and rural communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Fjaler
Target entity description: Fjaler is a small municipality in Western Norway known for its fjord landscapes and rural communities.
  • A. Fjell
    Fjell was a former municipality in Vestland county, Norway, encompassing coastal and island communities west of Bergen.
  • B. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • C. Lifjell
    Lifjell is a mountainous plateau and popular outdoor recreation area in Telemark, Norway, known for its hiking, skiing, and scenic alpine landscapes.
  • D. Follebu
    Follebu is a village in Innlandet county, Norway, known for its rural setting and traditional Norwegian countryside character within Gausdal municipality.
  • E. Flørli
    Flørli is a small, roadless village in Norway’s Lysefjord best known for its historic hydropower station and one of the world’s longest wooden stairways, with 4,444 steps climbing the mountainside.
  • 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_69feef7186d481909067f8088f3ea497 completed May 9, 2026, 8:25 a.m.
NEDg Description generation batch_69fef3374a34819094e0a4ac7bf89059 completed May 9, 2026, 8:41 a.m.
NED2 Entity disambiguation (via description) batch_69fef41c898881908ed3520643918445 completed May 9, 2026, 8:45 a.m.
Created at: April 10, 2026, 3:14 a.m.