Triple

T23147928
Position Surface form Disambiguated ID Type / Status
Subject Mirta Roses Periago E578243 entity
Predicate hasSurname P18 FINISHED
Object Roses Periago 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: Roses Periago | Statement: [Mirta Roses Periago, hasSurname, Roses Periago]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roses Periago
Context triple: [Mirta Roses Periago, hasSurname, Roses Periago]
  • A. Roses Periago chosen
    Roses Periago is the surname of Mirta Roses Periago, an Argentine epidemiologist and former Director of the Pan American Health Organization.
  • B. Rosa Elena
    Rosa Elena is a Mexican public figure best known as the wife of former president Felipe Calderón and for her involvement in high-profile political and legal controversies.
  • C. Rosina Jordana
    Rosina Jordana was the wife of renowned Spanish composer and pianist Isaac Albéniz, known primarily for her role in his personal and family life.
  • D. Rosana
    Rosana is a municipality in the state of São Paulo, Brazil, known for hosting a campus of São Paulo State University (UNESP).
  • E. Rosana
    Rosana is a Brazilian professional footballer known for her successful international career and contributions to top women’s clubs, including Avaldsnes IL.
  • 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_69e245fb8de081908f0eba7b5fd75bc4 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18ecf9e9881908991ede784158f1e completed April 29, 2026, 4:53 a.m.
Created at: April 17, 2026, 4:01 p.m.