Triple

T3556500
Position Surface form Disambiguated ID Type / Status
Subject Haugesund E75231 entity
Predicate near P350 FINISHED
Object Karmøy E77362 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: Karmøy | Statement: [Haugesund, near, Karmøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karmøy
Context triple: [Haugesund, near, Karmøy]
  • A. Karmøy chosen
    Karmøy is a large island and municipality in Rogaland county, Norway, known for its coastal fishing communities, maritime heritage, and historic Viking sites.
  • 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. Finnøy
    Finnøy is a small island municipality in Rogaland county, Norway, known as the rural birthplace of mathematician Niels Henrik Abel.
  • D. Nøtterøy
    Nøtterøy is a large, populated island and former municipality in Vestfold, Norway, situated in the Oslofjord and known for its coastal landscapes and residential communities.
  • E. Langøya
    Langøya is a large island in the Vesterålen archipelago in northern Norway, known for its dramatic coastal landscapes and fishing communities.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc057cc788190a6c4f3781f43abce completed March 8, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e4d4c92c8190b237746733b10e50 completed March 14, 2026, 4:32 a.m.
Created at: March 8, 2026, 3:20 p.m.