Triple

T22682903
Position Surface form Disambiguated ID Type / Status
Subject Veitvet E560827 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Økern NE NERFINISHED

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: Økern | Statement: [Veitvet, hasNeighbourhood, Økern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Økern
Context triple: [Veitvet, hasNeighbourhood, Økern]
  • A. Økern chosen
    Økern is a mixed residential and commercial neighborhood in Oslo, Norway, known for its shopping center, office developments, and transport connections.
  • B. Ekornes
    Ekornes is a Norwegian furniture manufacturer best known for its Stressless line of reclining chairs and sofas.
  • C. Kjørnes
    Kjørnes is a residential area and neighborhood within the municipality of Sogndal in Vestland county, Norway.
  • D. Støren
    Støren is a village in Trøndelag county, Norway, serving as a local commercial and transportation hub in the Gauldalen valley.
  • E. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2454d71b48190a1f80af9f82b6fcf completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1786204d88190a837a5f04e16e94c completed April 29, 2026, 3:17 a.m.
Created at: April 17, 2026, 3:12 p.m.