Triple

T8012213
Position Surface form Disambiguated ID Type / Status
Subject Troy Perkins E186520 entity
Predicate memberOfSportsTeam P330 FINISHED
Object Valerenga 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: Valerenga Fotball | Statement: [Troy Perkins, memberOfSportsTeam, Valerenga Fotball]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valerenga Fotball
Context triple: [Troy Perkins, memberOfSportsTeam, Valerenga Fotball]
  • A. Vålerenga
    Vålerenga is a neighborhood in Oslo, Norway, known for its working-class roots and strong association with the local football club Vålerenga Fotball.
  • B. 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.
  • C. Bryne FK
    Bryne FK is a Norwegian football club known for developing striker Erling Haaland in its youth system.
  • 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. 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.
  • 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_69ca82abaffc8190ab8af79cdbc31ab3 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3d73bf048190ad8066a7e95c34b0 completed March 31, 2026, 3:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc64982d08190976144beafcd231d completed April 2, 2026, 1:28 a.m.
Created at: March 30, 2026, 5:19 p.m.