Triple

T4416027
Position Surface form Disambiguated ID Type / Status
Subject San Diego Padres E94974 entity
Predicate notablePlayer P304 FINISHED
Object Dave Winfield E126842 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: Dave Winfield | Statement: [San Diego Padres, notablePlayer, Dave Winfield]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dave Winfield
Context triple: [San Diego Padres, notablePlayer, Dave Winfield]
  • A. Dave Winfield chosen
    Dave Winfield is a Hall of Fame American baseball player renowned for his stellar Major League career as a power-hitting outfielder and multi-sport collegiate star.
  • B. Cecil Fielder
    Cecil Fielder is a former American Major League Baseball slugger best known for his power-hitting seasons with the Detroit Tigers in the early 1990s.
  • C. Tom Seaver
    Tom Seaver was a Hall of Fame Major League Baseball pitcher, best known as the dominant ace of the New York Mets and one of the greatest right-handed pitchers in baseball history.
  • D. George Brett
    George Brett is a Hall of Fame third baseman widely regarded as one of the greatest hitters in Major League Baseball history.
  • E. Frank Thomas
    Frank Thomas was a prominent Disney animator and one of the famed "Nine Old Men," known for his influential work on many classic animated films.
  • 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_69b34539638c8190abfea3eb29425210 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3551afb448190a2ce2000193808ac completed March 13, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69b613664c548190b5cd0c2667baecc7 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:29 p.m.