Triple

T3185656
Position Surface form Disambiguated ID Type / Status
Subject Royal Audiencia of Lima E66691 entity
Predicate seatOfGovernment P761 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: [Royal Audiencia of Lima, seatOfGovernment, Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lima
Context triple: [Royal Audiencia of Lima, seatOfGovernment, Lima]
  • A. 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.
  • B. Sucre
    Sucre is the constitutional capital of Bolivia, known for its well-preserved colonial architecture and historical significance in the country’s independence.
  • C. Chiclayo
    Chiclayo is a major commercial and transportation hub in northern Peru, known for its nearby archaeological sites and vibrant regional culture.
  • D. Juliaca
    Juliaca is a major commercial and transportation hub in southern Peru, known for its bustling markets and proximity to Lake Titicaca.
  • E. Callao
    Callao is Peru’s chief seaport and a major coastal city adjacent to Lima, serving as the country’s principal gateway for maritime trade.
  • 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_69ad8587c1bc8190a2595f2c22ee1001 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada6c1341081909793f8d05fddfd5e completed March 8, 2026, 4:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bafeea081908b0909dff919a4fc completed March 12, 2026, 11:26 p.m.
Created at: March 8, 2026, 3:06 p.m.