Triple

T6216551
Position Surface form Disambiguated ID Type / Status
Subject Rogaland E139000 entity
Predicate hasMunicipality P847 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: [Rogaland, hasMunicipality, Karmøy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karmøy
Context triple: [Rogaland, hasMunicipality, 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. Skjervøy
    Skjervøy is a coastal fishing town and island community in northern Norway, known for its Arctic scenery and rich marine life.
  • D. Tromøya
    Tromøya is a large island off Norway’s southern coast, known for its scenic landscapes and proximity to the town of Arendal.
  • 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 (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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062a1eb3881908c7f735cf9c429ce completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3dd76508190aba82a4a74c74bea completed March 27, 2026, 1:56 a.m.
Created at: March 22, 2026, 4:21 p.m.