Triple

T21758684
Position Surface form Disambiguated ID Type / Status
Subject Surquillo District E537104 entity
Predicate partOf P40 FINISHED
Object Lima urban area 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 urban area | Statement: [Surquillo District, partOf, Lima urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima urban area
Context triple: [Surquillo District, partOf, Lima urban 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. Santiago City
    Santiago City is a highly urbanized commercial and industrial center in the Cagayan Valley region of the Philippines.
  • 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_69e0c46eab808190b848242d63a17c47 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01d902c9881908051904e44a136af completed April 28, 2026, 2:38 a.m.
Created at: April 16, 2026, 6:50 p.m.