Triple

T15694171
Position Surface form Disambiguated ID Type / Status
Subject Drag E380412 entity
Predicate locatedInAdministrativeTerritorialEntity P40 FINISHED
Object Hamarøy 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: Hamarøy | Statement: [Drag, locatedInAdministrativeTerritorialEntity, Hamarøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamarøy
Context triple: [Drag, locatedInAdministrativeTerritorialEntity, Hamarøy]
  • A. Hamarøy chosen
    Hamarøy is a coastal municipality in Nordland county, Norway, known for its dramatic fjord and mountain landscapes and its association with author Knut Hamsun.
  • B. Holsnøy
    Holsnøy is a large island in Vestland county, Norway, known for its rugged coastal landscape and proximity to the city of Bergen.
  • C. Spjærøy
    Spjærøy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday cottages.
  • D. Mosterøy
    Mosterøy is an island in Norway known for its coastal landscape and traditional West Norwegian island community.
  • E. Flekkerøy
    Flekkerøy is a populated island and coastal community in southern Norway, known for its maritime heritage and proximity to the city of Kristiansand.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f50ce848190a839c4fb7306d793 completed April 16, 2026, 2:54 a.m.
Created at: April 10, 2026, 4:44 a.m.