Triple

T5291160
Position Surface form Disambiguated ID Type / Status
Subject Vålerenga Fotball E119743 entity
Predicate hasNotableRivalryWith P893 FINISHED
Object Rosenborg BK E128344 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: Rosenborg BK | Statement: [Vålerenga Fotball, hasNotableRivalryWith, Rosenborg BK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rosenborg BK
Context triple: [Vålerenga Fotball, hasNotableRivalryWith, Rosenborg BK]
  • A. Rosenborg BK chosen
    Rosenborg BK is a Norwegian professional football club from Trondheim, historically one of the country’s most successful teams and a dominant force in the Eliteserien.
  • B. 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.
  • C. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • D. Viking FK
    Viking FK is a Norwegian professional football club based in Stavanger that competes in the country’s top division, the Eliteserien.
  • E. Molde FK
    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.
  • 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_69bd446de5648190b313a90bd96730d2 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd91aab9348190a373b30bb305f933 completed March 20, 2026, 6:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf77ac8e3c8190a846955a9eb65905 completed March 22, 2026, 5:01 a.m.
Created at: March 20, 2026, 1:52 p.m.