Triple

T18326841
Position Surface form Disambiguated ID Type / Status
Subject Fetsund Lenser E439031 entity
Predicate locatedNear P294 FINISHED
Object Øyeren 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: Øyeren | Statement: [Fetsund Lenser, locatedNear, Øyeren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Øyeren
Context triple: [Fetsund Lenser, locatedNear, Øyeren]
  • A. Øyeren chosen
    Øyeren is a large lake in southeastern Norway, known for its rich birdlife and role as a major reservoir along the Glomma river system.
  • B. Øye
    Øye is a small Norwegian village in the Sunnmøre region, known for its dramatic fjord landscape and the historic Hotel Union Øye.
  • C. Onsøy
    Onsøy is a former municipality and coastal district that now forms part of the city and municipality of Fredrikstad in Viken county, Norway.
  • D. Osøyro
    Osøyro is the administrative and commercial center of Bjørnafjorden Municipality in Vestland county, Norway.
  • E. Dyrøya
    Dyrøya is an island located in the Troms region of northern Norway, known for its rugged coastal landscape and small rural communities.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50aab3e7c81909b1c0a688707dfd6 completed April 19, 2026, 5:02 p.m.
Created at: April 10, 2026, 10:36 a.m.