Triple

T12876610
Position Surface form Disambiguated ID Type / Status
Subject Mitú E307984 entity
Predicate transportInfrastructure P1777 FINISHED
Object Mitú Airport
Mitú Airport is a regional public airport serving the remote town of Mitú in Colombia’s Vaupés Department, providing vital air connectivity to this isolated Amazonian area.
E1013714 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: Mitú Airport | Statement: [Mitú, transportInfrastructure, Mitú Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mitú Airport
Context triple: [Mitú, transportInfrastructure, Mitú Airport]
  • A. El Caraño Airport
    El Caraño Airport is the main public airport serving the city of Quibdó in Colombia’s Chocó Department.
  • B. Pichoy Airport
    Pichoy Airport is the main commercial airport serving the city of Valdivia in southern Chile.
  • C. Panguilemo Airport
    Panguilemo Airport is a regional public airport serving the city of Talca and the surrounding Maule Region in central Chile.
  • D. Čilipi Airport
    Čilipi Airport is the main international airport serving Dubrovnik and the surrounding southern Dalmatian region of Croatia.
  • E. Evelio Javier Airport
    Evelio Javier Airport is a small domestic airport in Antique province, Philippines, serving as an air gateway to Panay Island.
  • 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: Mitú Airport
Triple: [Mitú, transportInfrastructure, Mitú Airport]
Generated description
Mitú Airport is a regional public airport serving the remote town of Mitú in Colombia’s Vaupés Department, providing vital air connectivity to this isolated Amazonian area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mitú Airport
Target entity description: Mitú Airport is a regional public airport serving the remote town of Mitú in Colombia’s Vaupés Department, providing vital air connectivity to this isolated Amazonian area.
  • A. El Caraño Airport
    El Caraño Airport is the main public airport serving the city of Quibdó in Colombia’s Chocó Department.
  • B. Pichoy Airport
    Pichoy Airport is the main commercial airport serving the city of Valdivia in southern Chile.
  • C. Panguilemo Airport
    Panguilemo Airport is a regional public airport serving the city of Talca and the surrounding Maule Region in central Chile.
  • D. Čilipi Airport
    Čilipi Airport is the main international airport serving Dubrovnik and the surrounding southern Dalmatian region of Croatia.
  • E. Evelio Javier Airport
    Evelio Javier Airport is a small domestic airport in Antique province, Philippines, serving as an air gateway to Panay Island.
  • 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_69f6b8ccee708190bb4caa604386e3a3 completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6bafee83c819096469034ca32ff7d completed May 3, 2026, 3:03 a.m.
NED2 Entity disambiguation (via description) batch_69f6bb7a0ae08190813411fa677430aa completed May 3, 2026, 3:05 a.m.
Created at: April 9, 2026, 5:38 p.m.