Triple

T12243494
Position Surface form Disambiguated ID Type / Status
Subject Jack Roush E291792 entity
Predicate employer P7 FINISHED
Object Roush Performance E972392 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: Roush Performance | Statement: [Jack Roush, employer, Roush Performance]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roush Performance
Context triple: [Jack Roush, employer, Roush Performance]
  • A. Roush Racing chosen
    Roush Racing is a prominent American auto racing team, best known for its long-standing success in NASCAR competition.
  • B. Wood Brothers Racing
    Wood Brothers Racing is a historic and family-owned NASCAR team, founded in 1950, renowned for its innovative pit stop strategies and long-standing presence in stock car racing.
  • C. Hendrick Motorsports
    Hendrick Motorsports is a premier NASCAR racing organization known for its record-breaking success, multiple championships, and roster of legendary drivers.
  • D. Chip Ganassi Racing
    Chip Ganassi Racing is a prominent American auto racing organization that has fielded championship-winning teams across series such as IndyCar and NASCAR.
  • E. Hagan Racing
    Hagan Racing was a NASCAR Winston Cup Series team best known for fielding competitive cars for drivers like Neil Bonnett during the 1980s.
  • 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_69d6ab67950c8190be08450a06228c4b completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cb724448190be29fc1d2b946ab7 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e5ff68c81909d2796b24dd055f4 completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:51 p.m.