Triple

T12575610
Position Surface form Disambiguated ID Type / Status
Subject Don Mueang International Airport E300196 entity
Predicate focusCityFor P164 FINISHED
Object AirAsia 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 | Statement: [Don Mueang International Airport, focusCityFor, AirAsia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AirAsia
Context triple: [Don Mueang International Airport, focusCityFor, AirAsia]
  • 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. 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.
  • C. 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.
  • D. 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.
  • E. AirAsia India
    AirAsia India is a low-cost airline based in India that operates domestic flights across the country as part of the AirAsia group.
  • 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_69d7bde87b648190bcd0266e9efde098 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954a629fc8190a1c3b6777aad4527 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c6c21348190b851fce31df307e2 completed May 2, 2026, 10:36 p.m.
Created at: April 9, 2026, 4:47 p.m.