Triple

T15255097
Position Surface form Disambiguated ID Type / Status
Subject Valinhos E364624 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Jaguariúna E293529 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: Jaguariúna | Statement: [Valinhos, neighboringMunicipality, Jaguariúna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaguariúna
Context triple: [Valinhos, neighboringMunicipality, Jaguariúna]
  • A. Jaguariúna chosen
    Jaguariúna is a municipality in southeastern Brazil known for its agribusiness, technology industries, and popular rodeo festival.
  • B. Mengão
    Mengão is the popular nickname of Clube de Regatas do Flamengo, one of Brazil’s most successful and widely supported football clubs.
  • C. Itaparica
    Itaparica is a coastal municipality located on Itaparica Island in the state of Bahia, Brazil, known for its beaches and proximity to Salvador.
  • D. Maracanaú
    Maracanaú is an industrial and residential city in northeastern Brazil, located in the metropolitan region of Fortaleza in the state of Ceará.
  • E. Carriço
    Carriço is a civil parish within the municipality of Pombal in central Portugal, known for its rural character and local community life.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f8cb308190933c4478aa096e24 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fee5f7bd2081909c003deb3a692f18 completed May 9, 2026, 7:44 a.m.
Created at: April 10, 2026, 3:13 a.m.