Triple

T22827607
Position Surface form Disambiguated ID Type / Status
Subject Afonso E565702 entity
Predicate hasVariant P455 FINISHED
Object Affonso 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: Affonso | Statement: [Afonso, hasVariant, Affonso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Affonso
Context triple: [Afonso, hasVariant, Affonso]
  • A. Affonso chosen
    Affonso is a masculine given name of Portuguese origin commonly used in Brazil and other Lusophone countries.
  • B. Affonso Gonçalves
    Affonso Gonçalves is a Brazilian-American film editor known for his work on acclaimed independent films and collaborations with directors like Jim Jarmusch and Todd Haynes.
  • C. Affonso Eduardo
    Affonso Eduardo is the given name of Affonso Eduardo Reidy, a prominent Brazilian modernist architect known for influential public and residential projects in Rio de Janeiro.
  • D. Vítor
    Vítor is a Portuguese given name commonly used for men, equivalent to the English name Victor.
  • E. Athos Bulcão
    Athos Bulcão was a Brazilian artist renowned for his modernist tile panels and public art that became iconic elements of Brasília’s architectural landscape.
  • 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_69e24585ab1c81909b2b5065d15805d5 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17e2914188190be6cdbd8167cd806 completed April 29, 2026, 3:42 a.m.
Created at: April 17, 2026, 3:34 p.m.