Triple

T2720755
Position Surface form Disambiguated ID Type / Status
Subject CPTM commuter rail E60073 entity
Predicate connectsMunicipality P4245 FINISHED
Object Santo André E251826 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: Santo André | Statement: [CPTM commuter rail, connectsMunicipality, Santo André]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santo André
Context triple: [CPTM commuter rail, connectsMunicipality, Santo André]
  • A. Santo André chosen
    Santo André is a major industrial and residential city in the São Paulo metropolitan region of Brazil.
  • B. 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.
  • C. Mogi das Cruzes
    Mogi das Cruzes is a municipality in southeastern Brazil known as part of the Greater São Paulo metropolitan area and recognized for its industrial activity and agricultural production.
  • D. Taubaté
    Taubaté is a historic industrial and educational city in southeastern Brazil, located in the Paraíba Valley between São Paulo and Rio de Janeiro.
  • E. Osasco
    Osasco is a major industrial and commercial city in the metropolitan region of São Paulo, Brazil.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd1fc30c81909ac06588d50abdf8 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69b4cdb622788190bf419db993c2dd1f completed March 14, 2026, 2:53 a.m.
Created at: March 6, 2026, 9:55 p.m.