Triple

T4377907
Position Surface form Disambiguated ID Type / Status
Subject Surco E99052 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: [Surco, partOf, Metropolitan Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metropolitan Lima
Context triple: [Surco, partOf, Metropolitan Lima]
  • A. 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.
  • B. 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.
  • C. San José del Sur
    San José del Sur is a small lakeside community on Ometepe Island in Lake Nicaragua, known for its rural character and proximity to the island’s volcanic landscapes.
  • D. Chiclayo
    Chiclayo is a major commercial and transportation hub in northern Peru, known for its nearby archaeological sites and vibrant regional culture.
  • 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_69b3454ea8f48190a49c2436624d6ef6 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3523ed220819090cef1a7933489d9 completed March 12, 2026, 11:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd569f30088190bdc9ea72fe35be35 completed March 20, 2026, 2:15 p.m.
Created at: March 12, 2026, 11:18 p.m.