Triple

T16811981
Position Surface form Disambiguated ID Type / Status
Subject Vestre Toten E408636 entity
Predicate containsSettlement P847 FINISHED
Object Bøverbru E1062781 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: Bøverbru | Statement: [Vestre Toten, containsSettlement, Bøverbru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bøverbru
Context triple: [Vestre Toten, containsSettlement, Bøverbru]
  • A. Bøverbru chosen
    Bøverbru is a small village in Innlandet county, Norway, known for its rural setting and role as a local community center within Vestre Toten.
  • B. Bøvra
    Bøvra is a river in Lom Municipality in Innlandet county, Norway, known for flowing through a mountainous valley landscape.
  • C. Bøur
    Bøur is a small, picturesque village on the Faroe Islands known for its traditional turf-roofed houses and scenic views of nearby islets and sea cliffs.
  • D. Bøler
    Bøler is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its post-war apartment blocks, green surroundings, and access to the Østmarka forest.
  • E. Brüllingsen
    Brüllingsen is a small village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2d0793c81909d938ac174a6e63a completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b292a5888190812539b14eb77f34 completed May 10, 2026, 4:30 p.m.
Created at: April 10, 2026, 5:23 a.m.