Triple

T10248636
Position Surface form Disambiguated ID Type / Status
Subject Stefan Zweig E240283 entity
Predicate placeOfDeath P21 FINISHED
Object Petrópolis E248751 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: Petrópolis | Statement: [Stefan Zweig, placeOfDeath, Petrópolis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Petrópolis
Context triple: [Stefan Zweig, placeOfDeath, Petrópolis]
  • A. Petrópolis chosen
    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.
  • B. 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.
  • 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. Belford Roxo
    Belford Roxo is a municipality in the state of Rio de Janeiro, Brazil, located in the Baixada Fluminense region of the Rio de Janeiro metropolitan area.
  • E. Resende
    Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d23b620c8190b8a72d0eb0d16b93 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d71cbd67648190ba7faebd12d96ca9 completed April 9, 2026, 3:27 a.m.
Created at: April 6, 2026, 11:27 a.m.