Triple

T893439
Position Surface form Disambiguated ID Type / Status
Subject Brazil E19289 entity
Predicate formerCapital P3417 FINISHED
Object 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: Rio de Janeiro | Statement: [Brazil, formerCapital, Rio de Janeiro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio de Janeiro
Context triple: [Brazil, formerCapital, 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. São Paulo
    São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
  • C. Belo Horizonte
    Belo Horizonte is the capital and largest city of the Brazilian state of Minas Gerais, known for its modernist architecture, surrounding mountains, and vibrant cultural and economic life.
  • D. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • E. Salvador, Bahia, Brazil
    Salvador, the capital of Brazil’s Bahia state, is a major coastal city known for its Afro-Brazilian culture, colonial architecture, and historic role as the country’s first capital.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad212cd8819091eb1b7d606f5afd completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a0d31e8819091d3402546d8fa33 completed March 7, 2026, 1:37 p.m.
Created at: March 1, 2026, 7:39 p.m.