Triple

T23219154
Position Surface form Disambiguated ID Type / Status
Subject Antonio Roldán Betancourt Airport E580837 entity
Predicate locatedIn P40 FINISHED
Object Apartadó 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: Apartadó | Statement: [Antonio Roldán Betancourt Airport, locatedIn, Apartadó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apartadó
Context triple: [Antonio Roldán Betancourt Airport, locatedIn, Apartadó]
  • A. Apartadó chosen
    Apartadó is a municipality in Colombia’s Antioquia Department, known as an important agricultural and commercial center in the Urabá region, especially for banana production.
  • B. Cúcuta
    Cúcuta is a major Colombian city on the border with Venezuela, known as an important commercial and transportation hub in the northeast of the country.
  • C. Bucaramanga
    Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
  • D. Tunja
    Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
  • E. Montería
    Montería is a major Colombian city known as the capital of Córdoba Department, recognized for its cattle ranching economy and location along the Sinú River.
  • 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.