Triple

T6149069
Position Surface form Disambiguated ID Type / Status
Subject Stabæk Fotball E137150 entity
Predicate hasRival P1375 FINISHED
Object Vålerenga Fotball E22610 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: Vålerenga Fotball | Statement: [Stabæk Fotball, hasRival, Vålerenga Fotball]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vålerenga Fotball
Context triple: [Stabæk Fotball, hasRival, Vålerenga Fotball]
  • A. Vålerenga Fotball chosen
    Vålerenga Fotball is a Norwegian professional football club based in Oslo, known for its passionate fan base and history in the country’s top division.
  • B. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • 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. Sandefjord Fotball
    Sandefjord Fotball is a Norwegian professional football club based in the town of Sandefjord, known for competing in the country’s top divisions.
  • 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 (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_69c008a2c6308190a56519b22d55d083 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05ce21820819096be9159d6b70a5f completed March 22, 2026, 9:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e3cbf914819086c9553904aee0e5 completed March 27, 2026, 1:56 a.m.
Created at: March 22, 2026, 4:16 p.m.