Triple

T11499630
Position Surface form Disambiguated ID Type / Status
Subject CONCACAF Gold Cup Golden Boot E272629 entity
Predicate notableWinner P2766 FINISHED
Object Carlos Pavón E631985 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: Carlos Pavón | Statement: [CONCACAF Gold Cup Golden Boot, notableWinner, Carlos Pavón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlos Pavón
Context triple: [CONCACAF Gold Cup Golden Boot, notableWinner, Carlos Pavón]
  • A. Carlos Pavón chosen
    Carlos Pavón is a retired Honduran striker renowned as one of his country’s most prolific and iconic footballers, remembered especially for his crucial goals in international competition.
  • B. Rafael Navarro
    Rafael Navarro is a name shared by several notable individuals, including professionals in fields such as science, sports, and the arts.
  • C. Cristo Fernández
    Cristo Fernández is a Mexican actor and former professional footballer best known for playing the exuberant footballer Dani Rojas on the television series "Ted Lasso."
  • D. Óscar Pulido
    Óscar Pulido was a Mexican film and television actor known for his comedic roles during the Golden Age of Mexican cinema.
  • E. Juan Miguel Azpiroz
    Juan Miguel Azpiroz is a cinematographer best known for his work on the film "The Way."
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85de3e9c881909d6c55334f7a832d completed April 10, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69f64b7aff4c8190ba879e6c5632bb97 completed May 2, 2026, 7:07 p.m.
Created at: April 8, 2026, 9:36 p.m.