Triple

T2561908
Position Surface form Disambiguated ID Type / Status
Subject Nayib Bukele E57258 entity
Predicate hasSurname P18 FINISHED
Object Bukele E7161 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: Bukele | Statement: [Nayib Bukele, hasSurname, Bukele]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bukele
Context triple: [Nayib Bukele, hasSurname, Bukele]
  • A. Jair Marrufo
    Jair Marrufo is an American soccer referee who has officiated at the highest levels of Major League Soccer and international competitions.
  • B. Leon Guerrero
    Leon Guerrero is a surname most prominently associated with Lou Leon Guerrero, the first female governor of Guam and a notable Guamanian politician and businesswoman.
  • C. Mauricio
    Mauricio is a masculine given name, commonly used in Spanish- and Portuguese-speaking countries, derived from the Latin name Mauritius.
  • D. Nayib Bukele chosen
    Nayib Bukele is the President of El Salvador, known for his hardline security policies, populist style, and promotion of Bitcoin as legal tender.
  • E. Bustamante
    Bustamante is a Spanish-origin surname borne by numerous notable figures in politics, arts, and sports across the Spanish-speaking world.
  • 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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd336183c819084ed7de8ccc4c548 completed March 7, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69af655f72fc81908a85a69f95d0b827 completed March 10, 2026, 12:27 a.m.
Created at: March 6, 2026, 9:48 p.m.