Triple

T16728023
Position Surface form Disambiguated ID Type / Status
Subject WBGG E406512 entity
Predicate isHubFor P423 FINISHED
Object AirAsia (regional) E398414 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: AirAsia (regional) | Statement: [WBGG, isHubFor, AirAsia (regional)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AirAsia (regional)
Context triple: [WBGG, isHubFor, AirAsia (regional)]
  • A. AirAsia chosen
    AirAsia is a Malaysian low-cost airline known for its extensive network of domestic and international routes across Asia and beyond.
  • B. 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.
  • C. AirAsia Indonesia
    AirAsia Indonesia is a low-cost airline based in Indonesia and a subsidiary of the Malaysia-based AirAsia Group, operating domestic and international flights across Asia.
  • D. Philippines AirAsia
    Philippines AirAsia is a low-cost airline based in the Philippines and a subsidiary of the AirAsia Group, operating domestic and international flights across Asia.
  • E. AirAsia X
    AirAsia X is a Malaysian long-haul, low-cost airline that operates primarily out of Kuala Lumpur and serves destinations across Asia-Pacific and beyond.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e38749baa48190892b2e2b978f6eb6 completed April 18, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d483a8c8190b127f32dcc21be5a completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.