Triple

T12165522
Position Surface form Disambiguated ID Type / Status
Subject Villa El Salvador District E289823 entity
Predicate partOf P40 FINISHED
Object Metropolitan Lima E135326 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: Metropolitan Lima | Statement: [Villa El Salvador District, partOf, Metropolitan Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metropolitan Lima
Context triple: [Villa El Salvador District, partOf, Metropolitan Lima]
  • A. LaSalle-Peru metropolitan area
    The LaSalle-Peru metropolitan area is a small urban region in north-central Illinois centered on the twin cities of LaSalle and Peru and their surrounding communities.
  • B. Greater Lima conurbation chosen
    The Greater Lima conurbation is the large metropolitan area centered on Peru’s capital, Lima, encompassing numerous surrounding districts and cities in a continuous urban expanse.
  • C. Lima
    Lima is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • D. Lima
    Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
  • E. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • 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_69d6ab4d6c00819095a9a7c35de83cfb completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915d7109481908bf5fe512bba3c89 completed April 10, 2026, 3:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68e9fc934819089f68bcc823015da completed May 2, 2026, 11:54 p.m.
Created at: April 8, 2026, 9:50 p.m.