Triple

T2614231
Position Surface form Disambiguated ID Type / Status
Subject Super Bowl XLI E58848 entity
Predicate announcerPlayByPlayUS P7529 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: [Super Bowl XLI, announcerPlayByPlayUS, Jim Nantz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jim Nantz
Context triple: [Super Bowl XLI, announcerPlayByPlayUS, 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. 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.
  • D. 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.
  • E. Marv Albert
    Marv Albert is a renowned American sportscaster best known as the longtime voice of NBA basketball and a prominent play-by-play announcer across multiple major sports.
  • 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_69ab4ac444dc819099614e534dd6021f completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd87dcfbc8190b264062002bfe4ba completed March 7, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98b50fa08190abe65b53081cb06b completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:50 p.m.