Triple

T22758992
Position Surface form Disambiguated ID Type / Status
Subject Palácio Capanema E562931 entity
Predicate architect P184 FINISHED
Object Ernani Vasconcellos 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: Ernani Vasconcellos | Statement: [Palácio Capanema, architect, Ernani Vasconcellos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernani Vasconcellos
Context triple: [Palácio Capanema, architect, Ernani Vasconcellos]
  • A. Ernani Vasconcellos chosen
    Ernani Vasconcellos was a Brazilian architect known for his role in shaping modernist public architecture, including major government buildings in Brazil.
  • B. Heitor dos Prazeres
    Heitor dos Prazeres was a Brazilian painter, composer, and pioneering samba musician known for his vibrant depictions of Rio de Janeiro’s popular culture and Afro-Brazilian life.
  • C. Edson de Castro
    Edson de Castro was an American computer engineer and entrepreneur best known as the co-founder and driving force behind minicomputer manufacturer Data General.
  • D. João Baldasserini
    João Baldasserini is a Brazilian actor known for his work in film, television, and theater.
  • E. Franco da Rocha
    Franco da Rocha is a municipality in the metropolitan region of São Paulo, Brazil, known historically for its psychiatric hospital complex and growing urban development.
  • 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_69e24552e11c81909c2d61578a558bd7 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17a7a8ca481909953dcd6fbcc5fcf completed April 29, 2026, 3:26 a.m.
Created at: April 17, 2026, 3:25 p.m.