Triple

T22143862
Position Surface form Disambiguated ID Type / Status
Subject Recife metropolitan region E547234 entity
Predicate hasMunicipality P847 FINISHED
Object Igarassu NE NERFINISHED

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: Igarassu | Statement: [Recife metropolitan region, hasMunicipality, Igarassu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Igarassu
Context triple: [Recife metropolitan region, hasMunicipality, Igarassu]
  • A. Igarassu chosen
    Igarassu is one of Brazil’s oldest colonial towns, known for its historic churches and coastal location in the northeastern state of Pernambuco.
  • B. Igaratá
    Igaratá is a small municipality in the state of São Paulo, Brazil, known for its rural landscapes and reservoir that attracts tourism and outdoor recreation.
  • 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. Oriximiná
    Oriximiná is a large municipality in the Brazilian state of Pará, known for its Amazon rainforest areas, river systems, and significant mining and conservation sites.
  • E. Itatiba
    Itatiba is a municipality in southeastern Brazil known for its quality of life and proximity to the metropolitan region of Campinas in the state of São Paulo.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e3a95d88190a3bd80d9471976c3 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f129c045448190b3d189cdb8c0d2fd completed April 28, 2026, 9:42 p.m.
Created at: April 16, 2026, 8:32 p.m.