Triple

T10683937
Position Surface form Disambiguated ID Type / Status
Subject Santo André E251826 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Ribeirão Pires E368588 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: Ribeirão Pires | Statement: [Santo André, neighboringMunicipality, Ribeirão Pires]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ribeirão Pires
Context triple: [Santo André, neighboringMunicipality, Ribeirão Pires]
  • A. Ribeirão Pires chosen
    Ribeirão Pires is a municipality in the Greater São Paulo metropolitan region of Brazil, known for its green areas and role as a residential and service hub near the state capital.
  • B. Guaratinguetá
    Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
  • C. Laranjal Paulista
    Laranjal Paulista is a municipality in the state of São Paulo, Brazil, known for its riverside setting and regional agricultural activities.
  • D. Garça
    Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
  • E. Sertãozinho
    Sertãozinho is a municipality in the interior of Brazil known for its strong sugarcane-based agribusiness and ethanol production.
  • 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_69d9888cf7b481909de6a4fecb48cf4b completed April 10, 2026, 11:32 p.m.
Created at: April 8, 2026, 9:10 p.m.