Triple

T20183782
Position Surface form Disambiguated ID Type / Status
Subject Júlio Resende E492800 entity
Predicate familyName P18 FINISHED
Object Resende 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: Resende | Statement: [Júlio Resende, familyName, Resende]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Resende
Context triple: [Júlio Resende, familyName, Resende]
  • A. Resende chosen
    Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
  • B. Resende
    Resende is a municipality in the state of Rio de Janeiro, Brazil, known as an important industrial and regional center in the southern part of the state.
  • C. 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.
  • 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. Vassouras
    Vassouras is a historic municipality in the state of Rio de Janeiro, Brazil, known for its 19th-century coffee-era architecture and colonial heritage.
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668f068748190a0941e98ef5afd59 completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.