Triple

T1044384
Position Surface form Disambiguated ID Type / Status
Subject Arendal E22542 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Åmli
Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
E150931 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: Åmli | Statement: [Arendal, hasNeighbouringMunicipality, Åmli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åmli
Context triple: [Arendal, hasNeighbouringMunicipality, Åmli]
  • A. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • B. Elverum
    Elverum is a town and municipality in Innlandet county in eastern Norway, known for its forestry, military camp, and role in Norwegian World War II history.
  • C. Støre
    Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
  • D. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • E. Tøyen
    Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
  • 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: Åmli
Triple: [Arendal, hasNeighbouringMunicipality, Åmli]
Generated description
Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Åmli
Target entity description: Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
  • A. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • B. Elverum
    Elverum is a town and municipality in Innlandet county in eastern Norway, known for its forestry, military camp, and role in Norwegian World War II history.
  • C. Støre
    Støre is a Norwegian surname most prominently associated with Jonas Gahr Støre, the Prime Minister of Norway and leader of the Labour Party.
  • D. Drammen
    Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
  • E. Tøyen
    Tøyen is a neighborhood in Oslo, Norway, known for its cultural institutions, parks, and educational facilities.
  • 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b84937688190a5899af2104002df completed March 1, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf0e6f948190b5dc708884f20ab5 completed March 8, 2026, 12:13 a.m.
NEDg Description generation batch_69acbf77a3748190a510ea10d8ae4373 completed March 8, 2026, 12:14 a.m.
NED2 Entity disambiguation (via description) batch_69acbfe5eae88190ba65808402ada37f completed March 8, 2026, 12:16 a.m.
Created at: March 1, 2026, 7:42 p.m.