Triple

T18632492
Position Surface form Disambiguated ID Type / Status
Subject KB Karlskoga FF E455455 entity
Predicate location P40 FINISHED
Object Karlskoga, Sweden 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: Karlskoga, Sweden | Statement: [KB Karlskoga FF, location, Karlskoga, Sweden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karlskoga, Sweden
Context triple: [KB Karlskoga FF, location, Karlskoga, Sweden]
  • A. Karlskoga, Sweden
    Karlskoga, Sweden is an industrial town in central Sweden best known for its historic arms manufacturer Bofors and its association with Alfred Nobel.
  • B. Karlskoga chosen
    Karlskoga is an industrial town in central Sweden known for its historical association with Alfred Nobel and its role in the country’s arms and engineering industries.
  • C. Södertälje, Sweden
    Södertälje, Sweden is an industrial city southwest of Stockholm known for its major manufacturing plants, particularly in the automotive and heavy vehicle sectors.
  • D. Lund, Sweden
    Lund, Sweden is a historic university city in southern Sweden known for Lund University, its vibrant research and technology sector, and well-preserved medieval center.
  • E. Mora, Sweden
    Mora, Sweden is a small town in central Sweden’s Dalarna region, known for its traditional folk culture, wooden Dala horses, and as the home of painter Anders Zorn.
  • 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54fc5c7ec8190ab0c64f009583f96 completed April 19, 2026, 9:57 p.m.
Created at: April 10, 2026, 11:46 a.m.