Triple

T17180117
Position Surface form Disambiguated ID Type / Status
Subject Vannøya E416959 entity
Predicate partOf P40 FINISHED
Object Troms region 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: Troms region | Statement: [Vannøya, partOf, Troms region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troms region
Context triple: [Vannøya, partOf, Troms region]
  • A. Bodø region
    The Bodø region is a coastal area in Northern Norway centered around the city of Bodø, known for its Arctic landscape, maritime industries, and role as a regional hub for education, transport, and commerce.
  • B. Troms og Finnmark
    Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
  • C. Trysil region
    Trysil region is a mountainous forested area in eastern Norway known for its large ski resort and outdoor recreation opportunities.
  • D. Sør-Troms chosen
    Sør-Troms is a district in northern Norway encompassing several coastal and inland municipalities in the southern part of Troms county.
  • E. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3fc10afb48190a71f4a46f0280a14 completed April 18, 2026, 9:48 p.m.
Created at: April 10, 2026, 5:37 a.m.