Triple

T6226155
Position Surface form Disambiguated ID Type / Status
Subject Affonso Eduardo Reidy E139238 entity
Predicate hasWorkLocation P1527 FINISHED
Object Niterói E211032 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: Niterói | Statement: [Affonso Eduardo Reidy, hasWorkLocation, Niterói]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niterói
Context triple: [Affonso Eduardo Reidy, hasWorkLocation, Niterói]
  • A. Niterói chosen
    Niterói is a coastal city in the state of Rio de Janeiro, Brazil, known for its beaches, views of Rio across the bay, and iconic modernist architecture by Oscar Niemeyer.
  • B. Petrópolis
    Petrópolis is a historic mountain city in Brazil known as the former summer residence of the Brazilian imperial family and for its well-preserved 19th-century architecture.
  • C. Resende
    Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
  • D. São Gonçalo
    São Gonçalo is a large municipality in the state of Rio de Janeiro, Brazil, forming part of the metropolitan area of Rio de Janeiro and known for its dense urban character and industrial activity.
  • E. Macaé
    Macaé is a coastal city in southeastern Brazil known for its offshore oil industry and role as a major hub for petroleum exploration.
  • 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_69c008afd3148190b71e9eaa60420dd1 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062d5403081908effc8330bda3f0a completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d1171788190aa302b54d14e9a5d completed March 27, 2026, 7:09 a.m.
Created at: March 22, 2026, 4:22 p.m.