Triple

T12876508
Position Surface form Disambiguated ID Type / Status
Subject Puerto Leguízamo E307982 entity
Predicate hasAirport P105 FINISHED
Object Caucayá Airport
Caucayá Airport is a public airport serving the town of Puerto Leguízamo in the Putumayo Department of Colombia.
E1010182 NE FINISHED

How this triple was built (4 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: Caucayá Airport | Statement: [Puerto Leguízamo, hasAirport, Caucayá Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Caucayá Airport
Context triple: [Puerto Leguízamo, hasAirport, Caucayá Airport]
  • A. Palonegro International Airport
    Palonegro International Airport is the main commercial airport serving the city of Bucaramanga in northeastern Colombia.
  • B. Balbuena Military Airport
    Balbuena Military Airport was the earlier military airfield in Mexico City that evolved into today’s Mexico City International Airport.
  • C. Porvenir Airport
    Porvenir Airport is a small regional airport serving the town of Porvenir in the Chilean region of Tierra del Fuego.
  • D. Evelio Javier Airport
    Evelio Javier Airport is a small domestic airport in Antique province, Philippines, serving as an air gateway to Panay Island.
  • E. Guayaramerín Airport
    Guayaramerín Airport is a public airport serving the town of Guayaramerín in the Beni Department of northeastern Bolivia, near the border with Brazil.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Caucayá Airport
Triple: [Puerto Leguízamo, hasAirport, Caucayá Airport]
Generated description
Caucayá Airport is a public airport serving the town of Puerto Leguízamo in the Putumayo Department of Colombia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Caucayá Airport
Target entity description: Caucayá Airport is a public airport serving the town of Puerto Leguízamo in the Putumayo Department of Colombia.
  • A. Palonegro International Airport
    Palonegro International Airport is the main commercial airport serving the city of Bucaramanga in northeastern Colombia.
  • B. Balbuena Military Airport
    Balbuena Military Airport was the earlier military airfield in Mexico City that evolved into today’s Mexico City International Airport.
  • C. Porvenir Airport
    Porvenir Airport is a small regional airport serving the town of Porvenir in the Chilean region of Tierra del Fuego.
  • D. Evelio Javier Airport
    Evelio Javier Airport is a small domestic airport in Antique province, Philippines, serving as an air gateway to Panay Island.
  • E. Guayaramerín Airport
    Guayaramerín Airport is a public airport serving the town of Guayaramerín in the Beni Department of northeastern Bolivia, near the border with Brazil.
  • F. None of above. chosen

Provenance (5 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970f97f9c81908c75259a4cab1d3c completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a55161a881908d767653c17d3acc completed May 3, 2026, 1:30 a.m.
NEDg Description generation batch_69f6a772f3248190b18a2bda51ef4b65 completed May 3, 2026, 1:40 a.m.
NED2 Entity disambiguation (via description) batch_69f6a869e1908190bdc34fbadd226282 completed May 3, 2026, 1:44 a.m.
Created at: April 9, 2026, 5:38 p.m.