Triple

T21712544
Position Surface form Disambiguated ID Type / Status
Subject João Havelange E535940 entity
Predicate placeOfBirth P1 FINISHED
Object Rio de Janeiro, Brazil 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: Rio de Janeiro, Brazil | Statement: [João Havelange, placeOfBirth, Rio de Janeiro, Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio de Janeiro, Brazil
Context triple: [João Havelange, placeOfBirth, Rio de Janeiro, Brazil]
  • A. Rio de Janeiro chosen
    Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
  • B. Río de Janeiro
    Río de Janeiro is a station on Buenos Aires Underground Line A in Argentina’s capital city.
  • C. Lapa, Rio de Janeiro
    Lapa, Rio de Janeiro is a historic and bohemian neighborhood in central Rio known for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
  • D. Salvador, Bahia, Brazil
    Salvador, the capital of Brazil’s Bahia state, is a major coastal city known for its Afro-Brazilian culture, colonial architecture, and historic role as the country’s first capital.
  • E. Caju (Rio de Janeiro)
    Caju is a neighborhood in Rio de Janeiro, Brazil, known for its large port area, cemeteries, and proximity to the city’s industrial and docklands zones.
  • 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_69e0c46c6dd88190a595375fa6ebd701 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efb53573a08190ad73576d27e8094f completed April 27, 2026, 7:12 p.m.
Created at: April 16, 2026, 6:46 p.m.