Triple

T7609065
Position Surface form Disambiguated ID Type / Status
Subject Holmön archipelago E172185 entity
Predicate partOf P40 FINISHED
Object Västerbotten County E348319 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: Västerbotten County | Statement: [Holmön archipelago, partOf, Västerbotten County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Västerbotten County
Context triple: [Holmön archipelago, partOf, Västerbotten County]
  • A. Västerbotten County chosen
    Västerbotten County is a large administrative region in northern Sweden known for its vast forests, coastline along the Gulf of Bothnia, and sparsely populated inland areas.
  • B. Norrbotten County
    Norrbotten County is Sweden’s northernmost and largest county, known for its Arctic climate, vast wilderness, and sparsely populated landscapes.
  • C. Västernorrland County
    Västernorrland County is a coastal county in northern Sweden known for its forests, rivers, and towns such as Sundsvall and Härnösand.
  • D. Jämtland County
    Jämtland County is a large, sparsely populated region in central Sweden known for its mountains, forests, and popular outdoor tourism areas.
  • E. Gävleborg County
    Gävleborg County is a region in east-central Sweden along the Baltic coast, known for its mix of industrial towns, forests, and coastal landscapes.
  • 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_69c6994f50808190ba228764bb422417 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa1f6e888190ac6580724803fbc3 completed March 27, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9cf41d5308190be3ce32a4f7b707a completed March 30, 2026, 1:17 a.m.
Created at: March 27, 2026, 3:54 p.m.