Triple

T22122693
Position Surface form Disambiguated ID Type / Status
Subject Moreno E546711 entity
Predicate hasUsageRegion P908 FINISHED
Object Colombia NE NERFINISHED

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: [Moreno, hasUsageRegion, Colombia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colombia
Context triple: [Moreno, hasUsageRegion, 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. Costaguana
    Costaguana is the fictional South American republic created by Joseph Conrad as the turbulent political setting of his novel "Nostromo."
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e38b3848190ac3a4fa97d56e65a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1297f3fb48190b6aaca18b40c37ab completed April 28, 2026, 9:41 p.m.
Created at: April 16, 2026, 8:31 p.m.