Triple

T23399451
Position Surface form Disambiguated ID Type / Status
Subject Hammarby IF DFF E559461 entity
Predicate partOf P40 FINISHED
Object Hammarby IF 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: Hammarby IF | Statement: [Hammarby IF DFF, partOf, Hammarby IF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hammarby IF
Context triple: [Hammarby IF DFF, partOf, Hammarby IF]
  • A. Hammarby IF chosen
    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.
  • B. Malmö FF
    Malmö FF is one of Sweden’s most successful and popular football clubs, based in Malmö and known for its numerous national titles and regular participation in European competitions.
  • C. 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.
  • 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. Malmö IF
    Malmö IF is a Swedish professional ice hockey club from Malmö, historically known for competing in the country’s top leagues and later rebranding as the Malmö Redhawks.
  • 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_69e24549610c8190a069d6411ce5f661 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a4ddcb9481909881c77458c59c83 completed April 29, 2026, 6:27 a.m.
Created at: April 17, 2026, 5:37 p.m.