Triple

T3018733
Position Surface form Disambiguated ID Type / Status
Subject Gumbel E82401 entity
Predicate notableBearer P458 FINISHED
Object Greg Gumbel E13201 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: Greg Gumbel | Statement: [Gumbel, notableBearer, Greg Gumbel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greg Gumbel
Context triple: [Gumbel, notableBearer, Greg Gumbel]
  • A. Greg Gumbel chosen
    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.
  • B. Bryant Gumbel
    Bryant Gumbel is an American television journalist and sportscaster best known for co-hosting NBC's "Today" show and hosting HBO's "Real Sports with Bryant Gumbel."
  • C. 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.
  • D. Chris Berman
    Chris Berman is a longtime ESPN sportscaster best known for his energetic NFL coverage and signature catchphrases.
  • E. Jim Nantz
    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.
  • 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_69ad8b1fb34081908c1b873e2b7273e1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9a927b608190ba1392498507b237 completed March 8, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e71a9c08190848ecb3bcab18bb5 completed March 11, 2026, 8:57 a.m.
Created at: March 8, 2026, 3 p.m.