Triple

T11180638
Position Surface form Disambiguated ID Type / Status
Subject Griese E264528 entity
Predicate hasNotableBearer P458 FINISHED
Object Brian Griese E264530 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: Brian Griese | Statement: [Griese, hasNotableBearer, Brian Griese]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brian Griese
Context triple: [Griese, hasNotableBearer, Brian Griese]
  • A. Brian Griese chosen
    Brian Griese is a former American NFL quarterback who played primarily for the Denver Broncos and later became a football analyst and coach.
  • B. Matt Hasselbeck
    Matt Hasselbeck is a former NFL quarterback best known for leading the Seattle Seahawks to multiple playoff appearances and a Super Bowl berth in the 2000s.
  • C. Don Hasselbeck
    Don Hasselbeck is a former American football tight end who played in the NFL, notably for the New England Patriots, during the late 1970s and early 1980s.
  • D. Sarah Hasselbeck
    Sarah Hasselbeck is known as the wife of former NFL quarterback and sports analyst Matt Hasselbeck.
  • E. Tim Hasselbeck
    Tim Hasselbeck is a former NFL quarterback who later became a football analyst and commentator for ESPN.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8a7f35481909f35feb94ef10e80 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483affa988190bb7dc4f74d8e878c completed April 19, 2026, 7:26 a.m.
Created at: April 8, 2026, 9:29 p.m.