Triple

T13328375
Position Surface form Disambiguated ID Type / Status
Subject Åråsen Stadion E317500 entity
Predicate hasNickname P39 FINISHED
Object Åråsen
Åråsen is a football stadium in Lillestrøm, Norway, best known as the home ground of Lillestrøm SK.
E1034032 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: Åråsen | Statement: [Åråsen Stadion, hasNickname, Åråsen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åråsen
Context triple: [Åråsen Stadion, hasNickname, Åråsen]
  • A. 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.
  • B. Langåra
    Langåra is an island located within the municipality of Asker in Viken county, Norway.
  • C. Årnes
    Årnes is a small Norwegian town situated along the Glomma River, known as a local administrative and commercial center in Nes municipality in Viken county.
  • D. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • E. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • 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: Åråsen
Triple: [Åråsen Stadion, hasNickname, Åråsen]
Generated description
Åråsen is a football stadium in Lillestrøm, Norway, best known as the home ground of Lillestrøm SK.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Åråsen
Target entity description: Åråsen is a football stadium in Lillestrøm, Norway, best known as the home ground of Lillestrøm SK.
  • A. 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.
  • B. Langåra
    Langåra is an island located within the municipality of Asker in Viken county, Norway.
  • C. Årnes
    Årnes is a small Norwegian town situated along the Glomma River, known as a local administrative and commercial center in Nes municipality in Viken county.
  • D. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • E. Ormåsen
    Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992e4f908190a6f172bf910cffb8 completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69f71f2f69a88190b11e61a922786fc4 completed May 3, 2026, 10:10 a.m.
NEDg Description generation batch_69f71fe3cda881909916f7aac0664ead completed May 3, 2026, 10:13 a.m.
NED2 Entity disambiguation (via description) batch_69f72090b6b081908870801fdb679f57 completed May 3, 2026, 10:16 a.m.
Created at: April 9, 2026, 9:30 p.m.