Triple

T3738144
Position Surface form Disambiguated ID Type / Status
Subject Roger Penske E79634 entity
Predicate familyName P18 FINISHED
Object Penske E80854 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: Penske | Statement: [Roger Penske, familyName, Penske]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Penske
Context triple: [Roger Penske, familyName, Penske]
  • A. Penske Corporation chosen
    Penske Corporation is a diversified global transportation services company involved in truck leasing, logistics, automotive retail, and motorsports, founded and led by Roger Penske.
  • B. Penske Automotive Group
    Penske Automotive Group is a large international transportation services company and one of the world’s leading automotive and commercial truck retailers.
  • C. Roger Penske
    Roger Penske is an American businessman and former race car driver best known as the founder of Penske Corporation and a dominant figure in motorsports and automotive retail.
  • D. Haas
    Haas is a German-origin surname borne by numerous individuals worldwide, including several notable figures in fields such as sports, science, and the arts.
  • E. Triple Five Group
    Triple Five Group is a Canadian-based real estate conglomerate best known for developing and owning some of the world’s largest shopping and entertainment complexes, including the Mall of America and West Edmonton Mall.
  • 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_69ad8b115610819095b02007da5ca3cb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcb3e9248819098d481fe29e1c628 completed March 8, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f02aac60819095e62cc5e792d538 completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:34 p.m.