Triple

T20156468
Position Surface form Disambiguated ID Type / Status
Subject Kastellholmen E491580 entity
Predicate near P350 FINISHED
Object Djurgården 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: Djurgården | Statement: [Kastellholmen, near, Djurgården]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Djurgården
Context triple: [Kastellholmen, near, Djurgården]
  • A. Djurgården chosen
    Djurgården is a central Stockholm island known for its parks, museums, and major attractions like the Vasa Museum and Skansen.
  • B. Djurgårdens IF
    Djurgårdens IF is a prominent Swedish sports club from Stockholm, best known for its successful ice hockey and football teams and large, passionate fan base.
  • C. Hammarby IF
    Hammarby IF is a Swedish sports club from Stockholm best known for its passionate fan base and prominent football team competing in the country’s top divisions.
  • D. IFK Göteborg
    IFK Göteborg is a prominent Swedish football club based in Gothenburg, known for its domestic success and historic UEFA Cup victories.
  • E. Kalmar FF
    Kalmar FF is a professional Swedish football club based in the city of Kalmar that competes in the country’s top leagues and national competitions.
  • 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_69da6265f8f0819080b29c752a574088 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e0a0488190a25d92aaf300be4a completed April 20, 2026, 5:52 p.m.
Created at: April 11, 2026, 11:34 p.m.