Triple

T16504699
Position Surface form Disambiguated ID Type / Status
Subject Christian Michelsen E400894 entity
Predicate residence P75 FINISHED
Object Fjøsanger E1217496 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: Fjøsanger | Statement: [Christian Michelsen, residence, Fjøsanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fjøsanger
Context triple: [Christian Michelsen, residence, Fjøsanger]
  • A. Fjøsanger chosen
    Fjøsanger is a residential area in Bergen, Norway, historically known for its estates and as the place where former Norwegian Prime Minister Christian Michelsen died.
  • B. Fosnes
    Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
  • C. Sørenga
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • D. Leikanger
    Leikanger is a village and former municipality in Vestland county, Norway, situated along the Sognefjord and known for its fruit farming and scenic fjord landscape.
  • E. Fagernes
    Fagernes is a small town in central Norway that serves as a regional hub and gateway to the mountainous Valdres district.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e51ce1c81909548298f703a7ffa completed April 18, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00607e933c8190ae0572583b5a9cbf completed May 10, 2026, 10:39 a.m.
Created at: April 10, 2026, 5:14 a.m.