Triple

T128777
Position Surface form Disambiguated ID Type / Status
Subject Lima E2605 entity
Predicate locatedIn P40 FINISHED
Object Lima Province E14664 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 Province | Statement: [Lima, locatedIn, Lima Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima Province
Context triple: [Lima, locatedIn, Lima Province]
  • A. Lima Region chosen
    Lima Region is an administrative region on the central coast of Peru that surrounds but does not include the country’s capital city, Lima.
  • B. Limarí Province
    Limarí Province is an administrative division in north-central Chile known for its semi-arid climate, agriculture, and pisco-producing valleys.
  • C. Arequipa
    Arequipa is Peru’s second-largest city, known for its colonial architecture built from white volcanic stone and its dramatic setting beneath the Misti volcano.
  • D. Los Ríos Region
    Los Ríos Region is an administrative region in southern Chile known for its lakes, rivers, temperate rainforests, and the city of Valdivia as its capital.
  • E. 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.
  • 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_69a2520c0f3481908b0ed054a2fca8d0 completed Feb. 28, 2026, 2:25 a.m.
NER Named-entity recognition batch_69a2576518e0819096b35d8af7a4d1bd completed Feb. 28, 2026, 2:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2fa794c808190acf50a7eb90a012a completed Feb. 28, 2026, 2:23 p.m.
Created at: Feb. 28, 2026, 2:30 a.m.