Triple

T8795122
Position Surface form Disambiguated ID Type / Status
Subject Pão de Açúcar E209269 entity
Predicate viewIncludes P17987 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: [Pão de Açúcar, viewIncludes, Niterói]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Niterói
Context triple: [Pão de Açúcar, viewIncludes, 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. Teresópolis
    Teresópolis is a mountainous city in the state of Rio de Janeiro, Brazil, known for its cool climate, natural parks, and role as a popular ecotourism and weekend getaway destination.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa0c6008190a5c4d87510ad5bbd completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfab60ee608190af9f4aba631b42ef completed April 3, 2026, 11:58 a.m.
Created at: March 30, 2026, 6:43 p.m.