Triple

T17244567
Position Surface form Disambiguated ID Type / Status
Subject Chosica E418587 entity
Predicate isSuburbanAreaOf P294 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: [Chosica, isSuburbanAreaOf, Lima metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima metropolitan area
Context triple: [Chosica, isSuburbanAreaOf, 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 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.
  • C. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • D. Lima
    Lima is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • 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_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e22fb2c8190aea5d3872095bf46 completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01794102348190ba5906c011fd014b completed May 11, 2026, 6:37 a.m.
Created at: April 10, 2026, 5:39 a.m.