Triple

T15276342
Position Surface form Disambiguated ID Type / Status
Subject Sogn og Fjordane E365150 entity
Predicate administrativeCentre P1474 FINISHED
Object Leikanger E1174653 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: Leikanger | Statement: [Sogn og Fjordane, administrativeCentre, Leikanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leikanger
Context triple: [Sogn og Fjordane, administrativeCentre, Leikanger]
  • A. Leikanger chosen
    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.
  • B. Levanger
    Levanger is a historic town and municipality in Trøndelag county, Norway, known for its traditional wooden architecture and role as a regional commercial and educational center.
  • C. Bremanger
    Bremanger is a coastal municipality in Vestland county, Norway, known for its rugged fjord landscape, fishing communities, and scenic beaches like Grotlesanden.
  • D. Nissedal
    Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
  • E. Bjerkreim
    Bjerkreim is a rural municipality in southwestern Norway known for its rivers, salmon fishing, and agricultural landscape.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00952731c8190bf6a5e6e10c95b94 completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb02f505c81908e3982b67456e81c completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 3:14 a.m.