Triple

T17614151
Position Surface form Disambiguated ID Type / Status
Subject Kvinnherad Municipality E429039 entity
Predicate contains P35 FINISHED
Object Sæbøvik 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: Sæbøvik | Statement: [Kvinnherad Municipality, contains, Sæbøvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sæbøvik
Context triple: [Kvinnherad Municipality, contains, Sæbøvik]
  • A. Sæbøvik chosen
    Sæbøvik is a small village in western Norway located within the municipality of Kvinnherad in Vestland county.
  • B. Vedvik
    Vedvik is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
  • C. Vangsnes
    Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
  • D. Bøelva
    Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
  • E. Sørenga
    Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
  • 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.