Triple

T15870370
Position Surface form Disambiguated ID Type / Status
Subject Gilberto Silva E384814 entity
Predicate givenName P17 FINISHED
Object Gilberto E434837 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: Gilberto | Statement: [Gilberto Silva, givenName, Gilberto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gilberto
Context triple: [Gilberto Silva, givenName, Gilberto]
  • A. Gilberto chosen
    Gilberto is a masculine given name of Romance-language origin, commonly used in Italian, Spanish, and Portuguese-speaking countries.
  • B. Adalberto
    Adalberto is a masculine given name of Germanic origin, commonly used in Romance-language countries as a variant of Albert or Alberto.
  • C. Gustavo
    Gustavo is a masculine given name commonly used in Spanish- and Portuguese-speaking countries, equivalent to the name Gustaf.
  • D. Marcelo
    Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
  • E. Jorge
    Jorge is a key supporting character and leader of a rebel group in James Dashner’s dystopian Maze Runner sequel "The Scorch Trials."
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155f915788190a8efc3b3380cb829 completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbbff15c81909cb148a33b51a16e completed May 10, 2026, 1:13 a.m.
Created at: April 10, 2026, 4:50 a.m.