Triple

T19456350
Position Surface form Disambiguated ID Type / Status
Subject Ônibus 174 E486741 entity
Predicate cinematographyBy P1953 FINISHED
Object Walter Carvalho 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: Walter Carvalho | Statement: [Ônibus 174, cinematographyBy, Walter Carvalho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Carvalho
Context triple: [Ônibus 174, cinematographyBy, Walter Carvalho]
  • A. Walter Carvalho chosen
    Walter Carvalho is a renowned Brazilian cinematographer known for his visually striking work on acclaimed films such as "Behind the Sun."
  • B. Waldir Azevedo
    Waldir Azevedo was a Brazilian composer and virtuoso cavaquinho player best known for popularizing the choro genre with pieces like "Brasileirinho."
  • C. Jorge Machado Moreira
    Jorge Machado Moreira was a prominent Brazilian modernist architect and urban planner known for his influential role in mid-20th-century Brazilian architecture.
  • D. Carlos Alberto Moniz
    Carlos Alberto Moniz is a Portuguese musician, composer, and television personality known for his contributions to Portuguese popular music and entertainment.
  • E. Armando de Salles Oliveira
    Armando de Salles Oliveira was a Brazilian politician and journalist who served as the governor of São Paulo and played a key role in the development of higher education in the state.
  • 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_69d8e8d86d608190bd199a98d0297f27 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e633c4088881908f23f25a82a513f6 completed April 20, 2026, 2:10 p.m.
Created at: April 10, 2026, 1:38 p.m.