Triple

T11306830
Position Surface form Disambiguated ID Type / Status
Subject Jameson Nantz E267736 entity
Predicate childOf P120 FINISHED
Object Jim Nantz E53773 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: Jim Nantz | Statement: [Jameson Nantz, childOf, Jim Nantz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jim Nantz
Context triple: [Jameson Nantz, childOf, Jim Nantz]
  • A. Jim Nantz chosen
    Jim Nantz is a prominent American sportscaster best known for his long-running play-by-play coverage of major events such as the NFL, NCAA basketball, and The Masters on CBS.
  • B. Chris Berman
    Chris Berman is a longtime ESPN sportscaster best known for his energetic NFL coverage and signature catchphrases.
  • C. Brent Musburger
    Brent Musburger is an American sportscaster best known for his long career as a prominent play-by-play announcer and studio host covering major events across multiple sports.
  • D. Greg Gumbel
    Greg Gumbel is an American sportscaster best known for his long tenure with CBS Sports, where he has called NFL, NCAA basketball, and other major sporting events.
  • E. Al Michaels
    Al Michaels is a renowned American sportscaster best known for his decades of play-by-play commentary on NFL games and other major sporting events.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9bf87d88190904c2d174578ebbf completed April 9, 2026, 6:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d31322d48190aa93b7707ba6fb47 completed April 20, 2026, 7:17 a.m.
Created at: April 8, 2026, 9:32 p.m.