Triple

T15900054
Position Surface form Disambiguated ID Type / Status
Subject Aguarico Canton E385560 entity
Predicate borderCountry P224 FINISHED
Object Colombia E12035 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: Colombia | Statement: [Aguarico Canton, borderCountry, Colombia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colombia
Context triple: [Aguarico Canton, borderCountry, Colombia]
  • A. Colombia chosen
    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.
  • B. Colombia
    Colombia is a station on Madrid's Metro network, serving Line 8 and acting as an important interchange point in the city's public transportation system.
  • C. Chinchiná
    Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
  • D. 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.
  • E. Venezuela
    Venezuela is a South American country known for its vast oil reserves, diverse landscapes ranging from Caribbean coastlines to Andean mountains and Amazon rainforest, and its Spanish-speaking population.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1563cd2f081909404d724ecc8785a completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb04f3ea08190b5581768770677e8 completed May 9, 2026, 10:08 p.m.
Created at: April 10, 2026, 4:51 a.m.