Triple

T18308160
Position Surface form Disambiguated ID Type / Status
Subject Víctor Raúl Haya de la Torre E438544 entity
Predicate placeOfDeath P21 FINISHED
Object Lima, Peru 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: Lima, Peru | Statement: [Víctor Raúl Haya de la Torre, placeOfDeath, Lima, Peru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima, Peru
Context triple: [Víctor Raúl Haya de la Torre, placeOfDeath, Lima, Peru]
  • A. Lima
    Lima is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • B. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • C. Lima chosen
    Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
  • D. San Borja, Lima, Peru
    San Borja is an upper-middle-class residential and commercial district in Lima, Peru, known for its parks, cultural institutions, and modern urban development.
  • E. Cono Oeste of Lima
    Cono Oeste of Lima is a western metropolitan sector of Peru’s capital that groups several coastal and urban districts, including San Miguel, for planning and administrative purposes.
  • 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50215e0c48190a4679d432b6ee596 completed April 19, 2026, 4:25 p.m.
Created at: April 10, 2026, 10:35 a.m.