Triple

T18413598
Position Surface form Disambiguated ID Type / Status
Subject Trönö E441828 entity
Predicate locatedIn P40 FINISHED
Object Norrland 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: Norrland | Statement: [Trönö, locatedIn, Norrland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norrland
Context triple: [Trönö, locatedIn, Norrland]
  • A. Ångermanland
    Ångermanland is a historical province in northern Sweden known for its deep river valleys, forested landscapes, and coastal areas along the Gulf of Bothnia.
  • B. Jämtland region
    Jämtland region is a sparsely populated county in central Sweden known for its lakes, forests, mountains, and outdoor recreation tourism.
  • C. Götaland
    Götaland is one of Sweden’s three major historical lands, encompassing the country’s southern regions and several of its largest cities.
  • D. northern Sweden chosen
    Northern Sweden is a sparsely populated, subarctic region known for its vast forests, mountains, and traditional Sámi culture, including reindeer herding and indigenous languages.
  • E. Ostrobothnia
    Ostrobothnia is a coastal region in western Finland known for its strong Swedish-speaking population, flat landscapes, and historic maritime and agricultural traditions.
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a259c1c819094e710bb4a7ace75 completed April 19, 2026, 6:08 p.m.
Created at: April 10, 2026, 10:47 a.m.