Triple

T9805969
Position Surface form Disambiguated ID Type / Status
Subject Ronny Deila E237954 entity
Predicate managedClub P3239 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: [Ronny Deila, managedClub, Vålerenga Fotball]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vålerenga Fotball
Context triple: [Ronny Deila, managedClub, 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_69ca84dd4608819097ff4ed00feca280 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdab7b67748190ba16ce868f29d13e completed April 1, 2026, 11:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c45878e481908aa2098eceb44256 completed April 5, 2026, 2:09 a.m.
Created at: March 30, 2026, 8:29 p.m.