Triple

T11193296
Position Surface form Disambiguated ID Type / Status
Subject Instituto Geofísico del Perú E264855 entity
Predicate headquartersLocation P62 FINISHED
Object 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: Lima | Statement: [Instituto Geofísico del Perú, headquartersLocation, Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima
Context triple: [Instituto Geofísico del Perú, headquartersLocation, Lima]
  • A. Lima
    Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
  • 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 subregion of Portugal’s Vinho Verde wine area, known for producing fresh, aromatic white wines from local grape varieties.
  • D. Sucre
    Sucre is the constitutional capital of Bolivia, known for its well-preserved colonial architecture and historical significance in the country’s independence.
  • E. Chiclayo
    Chiclayo is a major commercial and transportation hub in northern Peru, known for its nearby archaeological sites and vibrant regional culture.
  • 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_69d6aa9eb9248190b20211772621b4bc completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8be025481909d311b587418dfb2 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ad00f9148190842bf587a2e4cbdf completed April 19, 2026, 10:22 a.m.
Created at: April 8, 2026, 9:29 p.m.