Triple

T3080449
Position Surface form Disambiguated ID Type / Status
Subject Jenderal Ahmad Yani International Airport E64243 entity
Predicate hasHubAirline P423 FINISHED
Object Citilink E159131 NE FINISHED

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: Citilink | Statement: [Jenderal Ahmad Yani International Airport, hasHubAirline, Citilink]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Citilink
Context triple: [Jenderal Ahmad Yani International Airport, hasHubAirline, Citilink]
  • A. Citilink chosen
    Citilink is an Indonesian low-cost airline operating domestic and regional flights as a subsidiary of the national carrier Garuda Indonesia.
  • B. UNI Air
    UNI Air is a Taiwanese regional airline that operates domestic and short-haul international flights, particularly within East Asia.
  • C. Air Orient
    Air Orient was a French airline of the early 20th century that operated long-distance routes, particularly to Asia, before becoming one of the companies merged to form Air France.
  • D. Thai AirAsia
    Thai AirAsia is a Thai low-cost airline operating domestic and international flights, and is part of the wider AirAsia group based in Southeast Asia.
  • E. IndiGo
    IndiGo is a major Indian low-cost airline known for its extensive domestic network, high on-time performance, and large fleet of Airbus A320-family aircraft.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1a9d61081909953eb2f4ad4537e completed March 8, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f89443a4819091dafc560b45cc26 completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:03 p.m.