Triple

T10683924
Position Surface form Disambiguated ID Type / Status
Subject Santo André E251826 entity
Predicate partOf P40 FINISHED
Object Greater São Paulo E284201 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: Greater São Paulo | Statement: [Santo André, partOf, Greater São Paulo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greater São Paulo
Context triple: [Santo André, partOf, Greater São Paulo]
  • A. São Paulo metropolitan area chosen
    The São Paulo metropolitan area is Brazil’s largest and most populous urban agglomeration, encompassing the city of São Paulo and numerous surrounding municipalities that form a major economic and cultural hub in Latin America.
  • B. São Paulo
    São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
  • C. São Bernardo do Campo
    São Bernardo do Campo is a major industrial city in Brazil known as a key center of the automotive industry within the São Paulo metropolitan area.
  • D. Recife metropolitan region
    The Recife metropolitan region is a major urban and economic hub in northeastern Brazil, centered on the city of Recife and encompassing numerous surrounding municipalities and neighborhoods.
  • 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 (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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fcc5134c8190bcb1d96a32634c17 completed April 9, 2026, 1:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbad00f7c8819097566994307c4550 completed April 12, 2026, 2:32 p.m.
Created at: April 8, 2026, 9:10 p.m.