Triple

T15932854
Position Surface form Disambiguated ID Type / Status
Subject Tena E386364 entity
Predicate hasAirport P105 FINISHED
Object Jumandy Airport
Jumandy Airport is a regional airport serving the city of Tena and the surrounding Amazonian area in Ecuador.
E1185804 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: Jumandy Airport | Statement: [Tena, hasAirport, Jumandy Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jumandy Airport
Context triple: [Tena, hasAirport, Jumandy Airport]
  • A. Mutiara Airport
    Mutiara Airport is a public airport in Palu, Central Sulawesi, Indonesia, serving as the main air gateway to the region.
  • B. Pangsuma Airport
    Pangsuma Airport is a regional airport serving the town of Putussibau in West Kalimantan, Indonesia.
  • C. Notohadinegoro Airport
    Notohadinegoro Airport is a regional public airport serving the city and regency of Jember in East Java, Indonesia.
  • D. Adisumarmo International Airport
    Adisumarmo International Airport is the main airport serving the city of Solo (Surakarta) in Central Java, Indonesia, handling both domestic and limited international flights.
  • E. Begumpet Airport
    Begumpet Airport is the former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.
  • 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: Jumandy Airport
Triple: [Tena, hasAirport, Jumandy Airport]
Generated description
Jumandy Airport is a regional airport serving the city of Tena and the surrounding Amazonian area in Ecuador.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jumandy Airport
Target entity description: Jumandy Airport is a regional airport serving the city of Tena and the surrounding Amazonian area in Ecuador.
  • A. Mutiara Airport
    Mutiara Airport is a public airport in Palu, Central Sulawesi, Indonesia, serving as the main air gateway to the region.
  • B. Pangsuma Airport
    Pangsuma Airport is a regional airport serving the town of Putussibau in West Kalimantan, Indonesia.
  • C. Notohadinegoro Airport
    Notohadinegoro Airport is a regional public airport serving the city and regency of Jember in East Java, Indonesia.
  • D. Adisumarmo International Airport
    Adisumarmo International Airport is the main airport serving the city of Solo (Surakarta) in Central Java, Indonesia, handling both domestic and limited international flights.
  • E. Begumpet Airport
    Begumpet Airport is the former primary airport of Hyderabad, India, now used mainly for military, training, and charter operations after being superseded by Rajiv Gandhi International Airport.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156a6d9b88190b461d12d69b12ac0 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffbe727c348190907c9e7a5db6031d completed May 9, 2026, 11:08 p.m.
NEDg Description generation batch_69ffbf3e80b08190899262a9d03c0e93 completed May 9, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_69ffbfc0d1548190b7d2e9e10e837f0b completed May 9, 2026, 11:14 p.m.
Created at: April 10, 2026, 4:53 a.m.