Triple

T13751291
Position Surface form Disambiguated ID Type / Status
Subject Andøya E330356 entity
Predicate hasMunicipality P847 FINISHED
Object Andøy E1082159 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: Andøy | Statement: [Andøya, hasMunicipality, Andøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andøy
Context triple: [Andøya, hasMunicipality, Andøy]
  • A. Andøy chosen
    Andøy is a municipality and island area in Nordland county, Norway, known for its Arctic landscapes, fishing communities, and whale-watching opportunities.
  • 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. Skjervøy
    Skjervøy is a coastal fishing town and island community in northern Norway, known for its Arctic scenery and rich marine life.
  • D. 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.
  • E. Askøy
    Askøy is a large island and municipality on Norway’s west coast, situated near Bergen and known for its coastal landscapes and commuter links to the city.
  • 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_69d81c573f288190aa2403d484fa3d49 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02148c208190a882927905a861a6 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_6a007d960bd08190b8ac366273646865 completed May 10, 2026, 12:44 p.m.
Created at: April 9, 2026, 10:08 p.m.