Triple

T13798523
Position Surface form Disambiguated ID Type / Status
Subject Løten municipality E331577 entity
Predicate hasSettlement P1068 FINISHED
Object Ådalsbruk E349208 NE FINISHED

How this triple was built (2 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: Ådalsbruk | Statement: [Løten municipality, hasSettlement, Ådalsbruk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ådalsbruk
Context triple: [Løten municipality, hasSettlement, Ådalsbruk]
  • A. Ådalsbruk chosen
    Ådalsbruk is a small village in Løten Municipality in Innlandet county, Norway, best known as the birthplace of painter Edvard Munch.
  • B. Haugen farm
    Haugen farm is the Norwegian site where the historic Tune Viking ship was unearthed.
  • C. Ålsgårde
    Ålsgårde is a coastal town in North Zealand, Denmark, known for its residential areas and proximity to the Øresund Strait.
  • D. Kornstadlandet
    Kornstadlandet is a Norwegian island located in Møre og Romsdal county, forming part of the coastal landscape of Averøy.
  • E. Akkerhaugen
    Akkerhaugen is a small village in Telemark, Norway, known for its scenic lakeside setting and role as a local hub for tourism and agriculture.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d81c58feb08190a77bca8bf7d6d20f completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de025ce9148190b23370f6a522ff7a completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b086d6d48190b823ed0a4403fbc5 completed May 3, 2026, 8:31 p.m.
Created at: April 9, 2026, 10:11 p.m.