Triple

T23276572
Position Surface form Disambiguated ID Type / Status
Subject Vegard Forren E588735 entity
Predicate memberOfSportsTeam P330 FINISHED
Object Molde FK 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: Molde FK | Statement: [Vegard Forren, memberOfSportsTeam, Molde FK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Molde FK
Context triple: [Vegard Forren, memberOfSportsTeam, Molde FK]
  • A. Molde FK chosen
    Molde FK is a Norwegian professional football club based in Molde, known as one of the country’s top teams and a key stepping stone in Erling Haaland’s early career.
  • B. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • C. Lillestrøm SK
    Lillestrøm SK is a Norwegian professional football club known for its passionate fan base, historic success in domestic competitions, and intense rivalry with other Oslo-area teams.
  • D. Strømsgodset
    Strømsgodset is a Norwegian professional football club based in Drammen, best known for competing in the country’s top division, the Eliteserien.
  • E. Stabæk Fotball
    Stabæk Fotball is a Norwegian professional football club based in Bærum, known for competing in the country’s top divisions and developing notable players and coaches.
  • 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_69e25d16e2c08190a291de254703129e completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19578adf48190bdb129a55f86172c completed April 29, 2026, 5:22 a.m.
Created at: April 17, 2026, 4:48 p.m.