Triple

T253467
Position Surface form Disambiguated ID Type / Status
Subject Northern Chile E5386 entity
Predicate borders P224 FINISHED
Object Peru E2033 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: Peru | Statement: [Northern Chile, borders, Peru]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peru
Context triple: [Northern Chile, borders, Peru]
  • A. Peru chosen
    Peru is a South American country known for its rich Inca heritage, diverse landscapes from Andes mountains to Amazon rainforest, and the iconic archaeological site of Machu Picchu.
  • B. Ecuador
    Ecuador is a South American country on the Pacific coast, known for its diverse geography that includes part of the Amazon rainforest, the Andean highlands, and the Galápagos Islands.
  • C. Chile
    Chile is a long, narrow South American country stretching along the Pacific coast, renowned for its diverse climates, stable economy, and world-class astronomical observatories.
  • D. Bolivia
    Bolivia is a landlocked country in central South America known for its diverse indigenous cultures, Andean and Amazonian landscapes, and administrative capitals La Paz and Sucre.
  • E. Colombia
    Colombia is a transcontinental country in northern South America, known for its diverse landscapes from Andes mountains to Amazon rainforest, rich cultural heritage, and major cities like Bogotá and Medellín.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d5331b48190b3797fece8e60e20 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ac7623e27c81909022abd9950753d1 completed March 7, 2026, 7:01 p.m.
Created at: Feb. 28, 2026, 2:55 a.m.