Triple

T11639737
Position Surface form Disambiguated ID Type / Status
Subject Tromsø Municipality E276627 entity
Predicate hasIsland P970 FINISHED
Object Reinøya (partly) E398902 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: Reinøya (partly) | Statement: [Tromsø Municipality, hasIsland, Reinøya (partly)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reinøya (partly)
Context triple: [Tromsø Municipality, hasIsland, Reinøya (partly)]
  • A. Reinøya chosen
    Reinøya is an island located within Porsangerfjorden in Troms og Finnmark county in northern Norway.
  • B. Rennesøy
    Rennesøy is an island and former municipality in Rogaland county, southwestern Norway, known for its coastal landscape and proximity to the city of Stavanger.
  • C. Rognøya
    Rognøya is an island located in the Norwegian lake Norsjø, known as part of the inland archipelago in Telemark.
  • D. Rebbenesøya
    Rebbenesøya is a coastal island in northern Norway, located in Troms county and known for its rugged landscapes, fishing communities, and Arctic maritime environment.
  • E. Rolløya
    Rolløya is an island located in Troms county in northern Norway, known for its rugged coastal landscape and Arctic climate.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a25e90c08190b7fb73939a2be3d7 completed April 10, 2026, 7:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69f019075f4c81908e0cde830231b229 completed April 28, 2026, 2:18 a.m.
Created at: April 8, 2026, 9:39 p.m.