Triple

T16103073
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Miraflores E390670 entity
Predicate locatedIn P40 FINISHED
Object city of Lima 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: city of Lima | Statement: [Municipality of Miraflores, locatedIn, city of Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Lima
Context triple: [Municipality of Miraflores, locatedIn, city of Lima]
  • A. city of Puno
    The city of Puno is a Peruvian urban center on the shores of Lake Titicaca, known as a cultural hub of the Andean highlands and a major site of traditional festivals and folklore.
  • 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
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • D. 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.
  • 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6976ec8190b499e99b196b0285 completed April 17, 2026, 9:37 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00077efdf48190ac26f433f6b17dbe completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5 a.m.