Triple

T8866571
Position Surface form Disambiguated ID Type / Status
Subject Niterói E211032 entity
Predicate faces P1699 FINISHED
Object City of Rio de Janeiro E6266 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: City of Rio de Janeiro | Statement: [Niterói, faces, City of Rio de Janeiro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Rio de Janeiro
Context triple: [Niterói, faces, City of Rio de Janeiro]
  • A. Rio de Janeiro chosen
    Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
  • B. Río de Janeiro
    Río de Janeiro is a station on Buenos Aires Underground Line A in Argentina’s capital city.
  • C. Niterói
    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.
  • D. 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.
  • E. Itaquera, São Paulo
    Itaquera, São Paulo is an eastern district of São Paulo best known for hosting Corinthians’ modern football stadium, a key venue from the 2014 FIFA World Cup.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6108530c819084559f4de669ce20 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69d139a069f881909cc59bad0f110830 completed April 4, 2026, 4:17 p.m.
Created at: March 30, 2026, 6:51 p.m.