Triple

T19444068
Position Surface form Disambiguated ID Type / Status
Subject Fabrizio E486426 entity
Predicate hasVariant P455 FINISHED
Object Fabricio NE NERFINISHED

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: Fabricio | Statement: [Fabrizio, hasVariant, Fabricio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fabricio
Context triple: [Fabrizio, hasVariant, Fabricio]
  • A. Fabrício
    Fabrício is the given name of Fabrício Werdum, a Brazilian mixed martial artist and former UFC heavyweight champion.
  • B. Fabricio Oberto chosen
    Fabricio Oberto is a retired Argentine professional basketball center best known for winning an NBA championship with the San Antonio Spurs and being part of Argentina’s golden generation that won Olympic gold in 2004.
  • C. Leonardo Salgado
    Leonardo Salgado is an Argentine paleontologist known for his work on large South American dinosaurs, including the description of Giganotosaurus.
  • D. Fabio Zamarion
    Fabio Zamarion is an Italian cinematographer known for his work on acclaimed contemporary Italian films.
  • E. Marcio
    Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d7ad488190a3373045029b0f3b completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63387e2048190bfb13fea434ddb46 completed April 20, 2026, 2:09 p.m.
Created at: April 10, 2026, 1:38 p.m.