Triple

T13291997
Position Surface form Disambiguated ID Type / Status
Subject Bremsnes E316580 entity
Predicate locatedIn P40 FINISHED
Object Averøya E79229 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: Averøya | Statement: [Bremsnes, locatedIn, Averøya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Averøya
Context triple: [Bremsnes, locatedIn, Averøya]
  • A. Averøya chosen
    Averøya is a scenic Norwegian island known for its coastal landscapes and its location along the famous Atlantic Ocean Road in Western Norway.
  • B. Spjærøy
    Spjærøy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday cottages.
  • C. Værøy
    Værøy is a small, scenic island and fishing community in northern Norway, known for its dramatic coastal landscapes and part of the Lofoten archipelago.
  • D. Andøy
    Andøy is a municipality and island area in Nordland county, Norway, known for its Arctic landscapes, fishing communities, and whale-watching opportunities.
  • E. Andøya
    Andøya is a large Norwegian island in Nordland county, known for its dramatic coastal landscapes, space center, and rich bird and whale-watching opportunities.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99077a8f48190b1163448a3a978a2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd3cf863fc81908723f7f6b3d45510 completed May 8, 2026, 1:31 a.m.
Created at: April 9, 2026, 9:27 p.m.