Triple

T12489473
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Region of Campinas E298523 entity
Predicate hasMunicipality P847 FINISHED
Object Valinhos E364624 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: Valinhos | Statement: [Metropolitan Region of Campinas, hasMunicipality, Valinhos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valinhos
Context triple: [Metropolitan Region of Campinas, hasMunicipality, Valinhos]
  • A. Valinhos chosen
    Valinhos is a municipality in southeastern Brazil known for its agricultural production, especially grapes and figs, and its proximity to the city of Campinas.
  • 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. Duas Barras
    Duas Barras is a small municipality in the mountainous interior of Rio de Janeiro state in southeastern Brazil.
  • E. Confins
    Confins is a municipality in the Brazilian state of Minas Gerais, best known for hosting the Belo Horizonte-Confins International Airport that serves the Belo Horizonte metropolitan area.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de1db9481909ddf70eb81cdb714 completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb63c80048190be87b41cdd4ac775 completed May 7, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:56 p.m.