Triple

T22602253
Position Surface form Disambiguated ID Type / Status
Subject Anderson Torres E574857 entity
Predicate appointedBy P257 FINISHED
Object Jair Bolsonaro 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: Jair Bolsonaro | Statement: [Anderson Torres, appointedBy, Jair Bolsonaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jair Bolsonaro
Context triple: [Anderson Torres, appointedBy, Jair Bolsonaro]
  • A. Jair Bolsonaro chosen
    Jair Bolsonaro is a far-right Brazilian politician and former army captain who served as the 38th President of Brazil from 2019 to 2022.
  • B. Michel Temer
    Michel Temer is a Brazilian lawyer and politician who served as the 37th President of Brazil from 2016 to 2018 following the impeachment of Dilma Rousseff.
  • C. Lula
    Lula is a feminine given name, often used in English-speaking countries and sometimes as a diminutive of names like Louise or Tallulah.
  • D. Pedro Rousseff
    Pedro Rousseff is the son of former Brazilian president Dilma Rousseff.
  • E. Jair
    Jair is a minor biblical judge of Israel mentioned in the Book of Judges, known for his leadership and his thirty sons who rode thirty donkeys and controlled thirty towns.
  • 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1626eb178819096866d03a78f82fc completed April 29, 2026, 1:44 a.m.
Created at: April 17, 2026, 2:50 p.m.