Triple

T23219165
Position Surface form Disambiguated ID Type / Status
Subject Antonio Roldán Betancourt Airport E580837 entity
Predicate servesRegion P82 FINISHED
Object Urabá 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: Urabá | Statement: [Antonio Roldán Betancourt Airport, servesRegion, Urabá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urabá
Context triple: [Antonio Roldán Betancourt Airport, servesRegion, Urabá]
  • A. Urabá region chosen
    The Urabá region is a strategic and biodiverse coastal area in northwestern Colombia, known for its banana production, Afro-Colombian and Indigenous communities, and role as a transit corridor between South and Central America.
  • B. Ciluba
    Ciluba is a Bantu language spoken primarily in the Democratic Republic of the Congo, especially in the Kasai region.
  • C. Rurrenabaque
    Rurrenabaque is a small Bolivian town known as a popular gateway to the Amazon rainforest and nearby Madidi National Park.
  • D. Humaitá
    Humaitá is a Brazilian riverside city in the state of Amazonas, known for its location along the Madeira River and its role as a regional hub in the western Amazon.
  • E. Humaitá
    Humaitá is a historic town in southern Paraguay known for its strategic role and heavily fortified position during the Paraguayan War.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f191675de48190858907872a065c56 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.