Triple

T21983672
Position Surface form Disambiguated ID Type / Status
Subject Natal metropolitan region E542902 entity
Predicate hasMunicipality P847 FINISHED
Object Parnamirim 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: Parnamirim | Statement: [Natal metropolitan region, hasMunicipality, Parnamirim]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parnamirim
Context triple: [Natal metropolitan region, hasMunicipality, Parnamirim]
  • A. Parnamirim chosen
    Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
  • B. Pinheiral
    Pinheiral is a small municipality in the state of Rio de Janeiro, Brazil, known for its rural character and growing role as a regional educational and residential center.
  • C. Guarapari
    Guarapari is a coastal resort city in southeastern Brazil known for its beaches and naturally radioactive monazite sand, which is popularly believed to have therapeutic properties.
  • D. Araruama
    Araruama is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its large saltwater lagoon and tourism.
  • E. Itanhaém
    Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
  • 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_69e0c48136b081908831fa907cc02e18 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12708055c8190b626ce244e368296 completed April 28, 2026, 9:30 p.m.
Created at: April 16, 2026, 8:04 p.m.