Triple

T21371853
Position Surface form Disambiguated ID Type / Status
Subject Köping E527084 entity
Predicate locatedIn P40 FINISHED
Object Västmanland County 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: Västmanland County | Statement: [Köping, locatedIn, Västmanland County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Västmanland County
Context triple: [Köping, locatedIn, Västmanland County]
  • A. Västmanland County chosen
    Västmanland County is an administrative region in central Sweden known for its mix of industrial towns, forests, and lakes.
  • B. Västmanland
    Västmanland is a historic province in central Sweden known for its forests, lakes, and long tradition of mining and metallurgy.
  • C. Södermanland County
    Södermanland County is an administrative region in east-central Sweden known for its mix of coastal landscapes, forests, and historic towns such as Nyköping and Eskilstuna.
  • 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. Uppsala County
    Uppsala County is an administrative region in east-central Sweden known for its historic university city of Uppsala and its mix of cultural heritage and rural landscapes.
  • 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_69e0b51e80808190ba5cb05667af02a9 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b0af44d88190aedd3b2127bb297d completed April 22, 2026, 11:27 a.m.
Created at: April 16, 2026, 5:10 p.m.