Triple

T7426458
Position Surface form Disambiguated ID Type / Status
Subject Red Bull Bragantino E171379 entity
Predicate homeCity P263 FINISHED
Object Bragança Paulista E340198 NE FINISHED

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: Bragança Paulista | Statement: [Red Bull Bragantino, homeCity, Bragança Paulista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bragança Paulista
Context triple: [Red Bull Bragantino, homeCity, Bragança Paulista]
  • A. Bragança Paulista chosen
    Bragança Paulista is a municipality in southeastern Brazil known for its historical architecture, mild climate, and role as a regional commercial and educational center.
  • B. Laranjal Paulista
    Laranjal Paulista is a municipality in the state of São Paulo, Brazil, known for its riverside setting and regional agricultural activities.
  • C. Bauru
    Bauru is a city in the state of São Paulo, Brazil, known as a regional economic and educational hub that hosts a campus of the University of São Paulo.
  • D. Barueri
    Barueri is a rapidly developing municipality in the São Paulo metropolitan area of Brazil, known for its strong commercial sector and high standard of living.
  • E. Taquaritinga
    Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69c68a63491881909281f73d4d5643bf completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f3055b7881908269ab909c5a85b5 completed March 27, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81f09787c819090b8be24070a7105 completed March 28, 2026, 6:33 p.m.
Created at: March 27, 2026, 3:12 p.m.