Triple

T13614435
Position Surface form Disambiguated ID Type / Status
Subject Bygland E325274 entity
Predicate containsSettlement P847 FINISHED
Object Åraksbø
Åraksbø is a small village in southern Norway located within the municipality of Bygland in Agder county.
E1080575 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: Åraksbø | Statement: [Bygland, containsSettlement, Åraksbø]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åraksbø
Context triple: [Bygland, containsSettlement, Åraksbø]
  • A. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • B. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • C. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • D. Ørskog
    Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
  • E. Engerdal
    Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
  • 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: Åraksbø
Triple: [Bygland, containsSettlement, Åraksbø]
Generated description
Åraksbø is a small village in southern Norway located within the municipality of Bygland in Agder county.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Åraksbø
Target entity description: Åraksbø is a small village in southern Norway located within the municipality of Bygland in Agder county.
  • A. Brårud
    Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
  • B. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • C. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • D. Ørskog
    Ørskog is a village and former municipality in western Norway, located in the county of Møre og Romsdal.
  • E. Engerdal
    Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0abe1208190a1e0a32dc141d836 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd08852a08190b9983e0c3058671a completed May 7, 2026, 5:48 p.m.
NEDg Description generation batch_69fcd4cc2f4c81909bd30cda58fc2393 completed May 7, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_69fcd5c128c0819081edf72e25c6bc98 completed May 7, 2026, 6:11 p.m.
Created at: April 9, 2026, 9:50 p.m.