Triple

T17614150
Position Surface form Disambiguated ID Type / Status
Subject Kvinnherad Municipality E429039 entity
Predicate contains P35 FINISHED
Object Dimmelsvik 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: Dimmelsvik | Statement: [Kvinnherad Municipality, contains, Dimmelsvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dimmelsvik
Context triple: [Kvinnherad Municipality, contains, Dimmelsvik]
  • A. Dimmelsvik chosen
    Dimmelsvik is a small village in Vestland county, Norway, situated within the municipality of Kvinnherad along the Hardangerfjorden.
  • B. Ottosdal
    Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
  • C. Tyssedal
    Tyssedal is a small industrial village in Vestland county, Norway, known for its historic hydropower facilities and scenic location by the Sørfjorden.
  • D. Dragsvik
    Dragsvik is a Finnish military locality known for hosting a key coastal garrison of the Finnish Navy.
  • E. Vangsnes
    Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d2fd96481908c9f3b566fca6907 completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.