Triple

T13067657
Position Surface form Disambiguated ID Type / Status
Subject Cotia E329369 entity
Predicate borderingEntity P224 FINISHED
Object Jandira E957674 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: Jandira | Statement: [Cotia, borderingEntity, Jandira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jandira
Context triple: [Cotia, borderingEntity, Jandira]
  • A. Jandira chosen
    Jandira is a municipality in the state of São Paulo, Brazil, located in the metropolitan region near the city of Barueri.
  • B. Jundiaí
    Jundiaí is a mid-sized industrial and logistics city in southeastern Brazil known for its strong economy and high quality of life.
  • C. Taquaritinga
    Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
  • D. Itapetininga
    Itapetininga is a municipality in southeastern Brazil known for its agricultural activities and regional commercial importance within the state of São Paulo.
  • E. Indaiatuba
    Indaiatuba is a rapidly growing municipality in southeastern Brazil known for its strong industrial base, high quality of life, and proximity to the city of Campinas.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ec8ba48190baf52c7823482680 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7396e6cf881908b4cc3836501ed08 completed May 3, 2026, 12:02 p.m.
Created at: April 9, 2026, 9 p.m.