Triple

T12510967
Position Surface form Disambiguated ID Type / Status
Subject Pueblo Libre District E299076 entity
Predicate partOf P40 FINISHED
Object Lima metropolitan area E2605 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: Lima metropolitan area | Statement: [Pueblo Libre District, partOf, Lima metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima metropolitan area
Context triple: [Pueblo Libre District, partOf, Lima metropolitan area]
  • 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. Lima
    Lima is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • 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. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • 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 (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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541d6e508190a4992f328e077467 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eac3ebd08190beb13fa00331f27b completed May 3, 2026, 6:27 a.m.
Created at: April 8, 2026, 9:57 p.m.