Triple

T21363254
Position Surface form Disambiguated ID Type / Status
Subject Oeiras E526837 entity
Predicate hasTwinTown P919 FINISHED
Object Belo Horizonte (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: Belo Horizonte (Brazil) | Statement: [Oeiras, hasTwinTown, Belo Horizonte (Brazil)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belo Horizonte (Brazil)
Context triple: [Oeiras, hasTwinTown, Belo Horizonte (Brazil)]
  • A. Belo Horizonte chosen
    Belo Horizonte is the capital and largest city of the Brazilian state of Minas Gerais, known for its modernist architecture, surrounding mountains, and vibrant cultural and economic life.
  • B. Curitiba
    Curitiba is the capital and largest city of the Brazilian state of Paraná, known for its innovative urban planning, extensive public transportation system, and high quality of life.
  • C. Brasília
    Brasília is the modernist-planned capital city of Brazil, known for its distinctive architecture and role as a major political and administrative center in South America.
  • D. Río de Janeiro
    Río de Janeiro is a station on Buenos Aires Underground Line A in Argentina’s capital city.
  • E. Guarulhos
    Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
  • 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_69e0b51d8a308190b09113b3b3f9bc15 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b06cbcb481909ec9014da3b0a18a completed April 22, 2026, 11:26 a.m.
Created at: April 16, 2026, 5:08 p.m.