Triple

T23136813
Position Surface form Disambiguated ID Type / Status
Subject Alberto da Veiga Guignard E577345 entity
Predicate placeOfBirth P1 FINISHED
Object Nova Friburgo 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: Nova Friburgo | Statement: [Alberto da Veiga Guignard, placeOfBirth, Nova Friburgo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nova Friburgo
Context triple: [Alberto da Veiga Guignard, placeOfBirth, Nova Friburgo]
  • A. Nova Friburgo chosen
    Nova Friburgo is a mountainous city in the state of Rio de Janeiro, Brazil, known for its Swiss-influenced architecture, cool climate, and textile industry.
  • B. Canoas
    Canoas is a major industrial and residential city in the Porto Alegre metropolitan region of Rio Grande do Sul, Brazil.
  • C. Novo Hamburgo
    Novo Hamburgo is a city in southern Brazil known for its strong German immigrant heritage and influential role in the country’s footwear industry.
  • D. Três Rios
    Três Rios is a municipality in the state of Rio de Janeiro, Brazil, known as a regional commercial and logistical hub at the confluence of three rivers.
  • E. Rosário
    Rosário is a municipality in the Brazilian state of Maranhão, known for its regional culture and role in the state's interior.
  • 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_69e245f8e6248190ba3d58e068b4dccb completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e8c33308190a44f98a7aab3b670 completed April 29, 2026, 4:52 a.m.
Created at: April 17, 2026, 4 p.m.