Triple

T21486279
Position Surface form Disambiguated ID Type / Status
Subject Håkøya, Norway E530123 entity
Predicate near P350 FINISHED
Object Tromsøya 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: Tromsøya | Statement: [Håkøya, Norway, near, Tromsøya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tromsøya
Context triple: [Håkøya, Norway, near, Tromsøya]
  • A. Tromøya
    Tromøya is a large island off Norway’s southern coast, known for its scenic landscapes and proximity to the town of Arendal.
  • B. Hamarøy
    Hamarøy is a coastal municipality in Nordland county, Norway, known for its dramatic fjord and mountain landscapes and its association with author Knut Hamsun.
  • C. Tromsøya island chosen
    Tromsøya island is a Norwegian island in Troms og Finnmark county that hosts the city center of Tromsø and is known for its Arctic location and vibrant cultural life.
  • D. Tjeldøya
    Tjeldøya is an island in northern Norway known for its rugged coastal landscape and location within the Ofoten region.
  • 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 (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_69e0c45acc3881908e38d3f28964152b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea370adc8190b79fe26e2eba1dca completed April 23, 2026, 9:45 a.m.
Created at: April 16, 2026, 6:22 p.m.