Triple

T13240062
Position Surface form Disambiguated ID Type / Status
Subject Sortland E315256 entity
Predicate hasNeighbour P5707 FINISHED
Object Øksnes E340039 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: Øksnes | Statement: [Sortland, hasNeighbour, Øksnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Øksnes
Context triple: [Sortland, hasNeighbour, Øksnes]
  • A. Øksnes chosen
    Øksnes is a coastal municipality in Nordland county, Norway, known for its fishing communities and location within the Vesterålen archipelago.
  • 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. Kvitsøy
    Kvitsøy is a small island municipality in southwestern Norway known for its maritime heritage, lighthouse, and rich coastal fishing grounds.
  • E. Hamnøy
    Hamnøy is a picturesque fishing village and island in Norway’s Lofoten archipelago, renowned for its dramatic mountain scenery and iconic red rorbuer cabins.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d5850ac8190849a51da39efe5be completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd08698e0819084f3098d471e7dc9 completed May 7, 2026, 5:48 p.m.
Created at: April 9, 2026, 9:23 p.m.