Triple

T19456352
Position Surface form Disambiguated ID Type / Status
Subject Ônibus 174 E486741 entity
Predicate musicBy P1952 FINISHED
Object João Nabuco 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: João Nabuco | Statement: [Ônibus 174, musicBy, João Nabuco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: João Nabuco
Context triple: [Ônibus 174, musicBy, João Nabuco]
  • A. João Nabuco chosen
    João Nabuco is a Brazilian composer and musician known for creating the score for the documentary film "Bus 174."
  • B. Zequinha de Abreu
    Zequinha de Abreu was a Brazilian composer and musician best known for his influential choro works that became classics of Brazilian popular music.
  • C. Joaquim Nabuco
    Joaquim Nabuco was a prominent Brazilian diplomat, writer, and leading abolitionist who played a key role in the movement to end slavery in Brazil.
  • D. Otto de Alencar Chaves
    Otto de Alencar Chaves is a Brazilian individual notable for bearing the surname Chaves, likely recognized in a professional or public capacity in Brazil.
  • E. José Pinheiro de Azevedo
    José Pinheiro de Azevedo was a Portuguese naval officer and politician who served as prime minister during the turbulent post-Carnation Revolution transitional period in the mid-1970s.
  • 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.