Triple

T23355731
Position Surface form Disambiguated ID Type / Status
Subject Janne Jönsson E593041 entity
Predicate employer P7 FINISHED
Object Stabæk Fotball 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: Stabæk Fotball | Statement: [Janne Jönsson, employer, Stabæk Fotball]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stabæk Fotball
Context triple: [Janne Jönsson, employer, Stabæk Fotball]
  • A. Stabæk Fotball chosen
    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.
  • B. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • C. Strømsgodset
    Strømsgodset is a Norwegian professional football club based in Drammen, best known for competing in the country’s top division, the Eliteserien.
  • D. 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.
  • E. Viking FK
    Viking FK is a Norwegian professional football club based in Stavanger that competes in the country’s top division, the Eliteserien.
  • 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_69e25d24d2a4819092e6ede74c2a918d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19a176b548190bf5a08bb2585344d completed April 29, 2026, 5:41 a.m.
Created at: April 17, 2026, 5:26 p.m.