Triple

T2941256
Position Surface form Disambiguated ID Type / Status
Subject Vasa Museum E79390 entity
Predicate locatedIn P40 FINISHED
Object Djurgården E77996 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: Djurgården | Statement: [Vasa Museum, locatedIn, Djurgården]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Djurgården
Context triple: [Vasa Museum, locatedIn, 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. IFK Göteborg
    IFK Göteborg is a prominent Swedish football club based in Gothenburg, known for its domestic success and historic UEFA Cup victories.
  • D. Östersunds FK
    Östersunds FK is a Swedish professional football club known for its rapid rise through the leagues and notable performances in domestic and European competitions.
  • E. Örgryte IS
    Örgryte IS is a Swedish sports club best known for its historic football team, one of the oldest in Sweden, based in Gothenburg.
  • 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_69ad8b1089588190b74d9e2505e45762 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9870e5d08190b3b277ba823fe6a1 completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b08689ec3481909d9f039069ff19c7 completed March 10, 2026, 9 p.m.
Created at: March 8, 2026, 2:56 p.m.