Triple

T14685008
Position Surface form Disambiguated ID Type / Status
Subject Golden Boot Award E344886 entity
Predicate hasCategory P87 FINISHED
Object men's Golden Boot E538831 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: men's Golden Boot | Statement: [Golden Boot Award, hasCategory, men's Golden Boot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: men's Golden Boot
Context triple: [Golden Boot Award, hasCategory, men's Golden Boot]
  • A. MLS Golden Boot
    The MLS Golden Boot is Major League Soccer’s annual award given to the league’s top goal scorer in the regular season.
  • B. Golden Boot
    The Golden Boot is a football award given to the top goal scorer at major tournaments, including the FIFA Club World Cup.
  • C. FIFA World Cup Silver Shoe
    The FIFA World Cup Silver Shoe is an individual football award given to the tournament’s second-highest goal scorer.
  • D. FIFA World Cup Golden Boot chosen
    The FIFA World Cup Golden Boot is the award given to the tournament's top goal scorer.
  • E. FIFA Club World Cup Golden Boot
    The FIFA Club World Cup Golden Boot is an annual football award given to the top goal scorer at the FIFA Club World Cup tournament.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb56bdb8081909ff86440ba20fb1f completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde18592088190892ae1cc371165be completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:28 a.m.