Triple

T15276364
Position Surface form Disambiguated ID Type / Status
Subject Sogn og Fjordane E365150 entity
Predicate containsPart P35 FINISHED
Object Årdal
Årdal is a municipality in western Norway known for its dramatic fjord and mountain scenery and its aluminum industry.
E666044 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: Årdal | Statement: [Sogn og Fjordane, containsPart, Årdal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Årdal
Context triple: [Sogn og Fjordane, containsPart, Årdal]
  • A. Årdal
    Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
  • B. Øvre Årdal
    Øvre Årdal is a small industrial village in Vestland county, Norway, known as a gateway to the Jotunheimen mountain area and its popular hiking routes.
  • C. Naustdal
    Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
  • D. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • E. Sunndalsøra
    Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
  • 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: Årdal
Triple: [Sogn og Fjordane, containsPart, Årdal]
Generated description
Årdal is a municipality in western Norway known for its dramatic fjord and mountain scenery and its aluminum industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Årdal
Target entity description: Årdal is a municipality in western Norway known for its dramatic fjord and mountain scenery and its aluminum industry.
  • A. Årdal chosen
    Årdal is a municipality in Vestland county, Norway, known for its dramatic fjord landscape, hydroelectric power production, and aluminum industry.
  • B. Øvre Årdal
    Øvre Årdal is a small industrial village in Vestland county, Norway, known as a gateway to the Jotunheimen mountain area and its popular hiking routes.
  • C. Naustdal
    Naustdal is a small coastal village and former municipality in Vestland county, western Norway, known for its fjord landscape and salmon-rich Nausta River.
  • D. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • E. Sunndalsøra
    Sunndalsøra is a village and industrial center in western Norway known for its aluminum production and dramatic fjord and mountain surroundings.
  • F. None of above.

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_69ff6ec2f35c8190a96af080cd7b6d0e completed May 9, 2026, 5:28 p.m.
NEDg Description generation batch_69ff6f3dded48190a5ede571862de057 completed May 9, 2026, 5:30 p.m.
NED2 Entity disambiguation (via description) batch_69ff6fa74b1c8190a7ceb63943639793 completed May 9, 2026, 5:32 p.m.
Created at: April 10, 2026, 3:14 a.m.