Triple

T23498504
Position Surface form Disambiguated ID Type / Status
Subject BRCOB E571768 entity
Predicate serves P98 FINISHED
Object Corumbá metropolitan area — NE NERFINISHED

How this triple was built (3 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: Corumbá metropolitan area | Statement: [BRCOB, serves, Corumbá metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Corumbá metropolitan area
Context triple: [BRCOB, serves, Corumbá metropolitan area]
  • A. Metropolitan Region of Caxias do Sul
    The Metropolitan Region of Caxias do Sul is an officially designated metropolitan area in Rio Grande do Sul, Brazil, centered around the industrial city of Caxias do Sul and its surrounding municipalities.
  • B. Londrina metropolitan area
    The Londrina metropolitan area is a major urban and economic region in northern Paraná, Brazil, centered around the city of Londrina and its surrounding municipalities.
  • C. Metropolitan Region of Porto Alegre
    The Metropolitan Region of Porto Alegre is a major urban and economic agglomeration in the state of Rio Grande do Sul, Brazil, centered on the city of Porto Alegre and encompassing numerous surrounding municipalities.
  • D. Metropolitan Region of Campinas
    The Metropolitan Region of Campinas is a major urban and economic agglomeration in the state of São Paulo, Brazil, centered around the city of Campinas and encompassing several surrounding municipalities.
  • E. Magé
    Magé is a municipality in the state of Rio de Janeiro, Brazil, located in the metropolitan region of Rio de Janeiro and known for its coastal setting and historical significance.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Corumbá metropolitan area
Target entity description: The Corumbá metropolitan area is an urban region in the Brazilian state of Mato Grosso do Sul centered on the city of Corumbá, near the Bolivian border and the Pantanal wetlands.
  • A. Metropolitan Region of Caxias do Sul
    The Metropolitan Region of Caxias do Sul is an officially designated metropolitan area in Rio Grande do Sul, Brazil, centered around the industrial city of Caxias do Sul and its surrounding municipalities.
  • B. Londrina metropolitan area
    The Londrina metropolitan area is a major urban and economic region in northern Paraná, Brazil, centered around the city of Londrina and its surrounding municipalities.
  • C. Metropolitan Region of Porto Alegre
    The Metropolitan Region of Porto Alegre is a major urban and economic agglomeration in the state of Rio Grande do Sul, Brazil, centered on the city of Porto Alegre and encompassing numerous surrounding municipalities.
  • D. Metropolitan Region of Campinas
    The Metropolitan Region of Campinas is a major urban and economic agglomeration in the state of São Paulo, Brazil, centered around the city of Campinas and encompassing several surrounding municipalities.
  • E. Magé
    Magé is a municipality in the state of Rio de Janeiro, Brazil, located in the metropolitan region of Rio de Janeiro and known for its coastal setting and historical significance.
  • F. None of above. chosen

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_69e245b4829881909b77a70e942bbd54 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a7e184ec8190aff3677c9b00a8f2 completed April 29, 2026, 6:40 a.m.
Created at: April 17, 2026, 6:06 p.m.