Triple

T22478543
Position Surface form Disambiguated ID Type / Status
Subject Lillestrøm municipality E555698 entity
Predicate hasSportsClub P346 FINISHED
Object Lillestrøm SK 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: Lillestrøm SK | Statement: [Lillestrøm municipality, hasSportsClub, Lillestrøm SK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lillestrøm SK
Context triple: [Lillestrøm municipality, hasSportsClub, Lillestrøm SK]
  • A. Lillestrøm SK chosen
    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.
  • B. Strømsgodset
    Strømsgodset is a Norwegian professional football club based in Drammen, best known for competing in the country’s top division, the Eliteserien.
  • C. Lillestrøm
    Lillestrøm is a Norwegian town and former municipality in the Greater Oslo Region, known as a regional commercial center and transport hub.
  • D. Sarpsborg 08 FF
    Sarpsborg 08 FF is a Norwegian professional football club based in Sarpsborg that competes in the country’s top division, the Eliteserien.
  • E. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • 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_69e11e52c2048190952dc5df209b9bed completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15be653bc8190a2e5c47e38228bfe completed April 29, 2026, 1:16 a.m.
Created at: April 16, 2026, 8:49 p.m.