Triple

T15547486
Position Surface form Disambiguated ID Type / Status
Subject Atibaia E370647 entity
Predicate nearbyCity P350 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: [Atibaia, nearbyCity, Bragança Paulista]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bragança Paulista
Context triple: [Atibaia, nearbyCity, 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a9073948190b6e9cf504aacc7cf completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82e56ffc81909e3228a660df4e09 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:08 a.m.