Triple

T12401634
Position Surface form Disambiguated ID Type / Status
Subject Jesús María District E296267 entity
Predicate isUrbanAreaOf P12103 FINISHED
Object Lima city core E569675 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 city core | Statement: [Jesús María District, isUrbanAreaOf, Lima city core]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima city core
Context triple: [Jesús María District, isUrbanAreaOf, Lima city core]
  • A. 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.
  • B. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • C. Lima
    Lima is a subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • D. 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.
  • E. Lima District chosen
    Lima District is the historic and administrative center of Peru’s capital city, encompassing the main government institutions, colonial core, and principal civic and commercial areas of Lima.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d477004819095e65ef6f70c69d9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e256fe408190bd40b62eb51b6ef9 completed May 3, 2026, 5:51 a.m.
Created at: April 8, 2026, 9:55 p.m.