Triple

T1027823
Position Surface form Disambiguated ID Type / Status
Subject San Isidro E22180 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: [San Isidro, partOf, Lima Metropolitan Area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima Metropolitan Area
Context triple: [San Isidro, partOf, Lima Metropolitan Area]
  • A. 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.
  • B. Callao
    Callao is Peru’s chief seaport and a major coastal city adjacent to Lima, serving as the country’s principal gateway for maritime trade.
  • C. Santiago Metropolitan Region
    The Santiago Metropolitan Region is Chile’s most populous and economically significant administrative region, encompassing the nation’s capital city of Santiago.
  • D. Samborondón metropolitan area
    The Samborondón metropolitan area is a rapidly growing, affluent suburban and commercial zone adjacent to Guayaquil in Ecuador, known for its gated communities, shopping centers, and business developments.
  • E. Santiago de Surco
    Santiago de Surco is a large, predominantly residential and commercial district in southern Lima, Peru, known for its middle- to upper-class neighborhoods, shopping centers, and educational institutions.
  • 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_69a493d6e380819097b384986ffc315c completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7f6ff048190863f9c38162d09b7 completed March 1, 2026, 10:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac661d6d4c8190a72cd52ec2a27e12 completed March 7, 2026, 5:53 p.m.
Created at: March 1, 2026, 7:41 p.m.