Triple

T19414855
Position Surface form Disambiguated ID Type / Status
Subject Tony Fernandes E485685 entity
Predicate employer P7 FINISHED
Object AirAsia Group NE NERFINISHED

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 Group | Statement: [Tony Fernandes, employer, AirAsia Group]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AirAsia Group
Context triple: [Tony Fernandes, employer, AirAsia Group]
  • 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. Malaysia Aviation Group
    Malaysia Aviation Group is a Malaysian state-owned aviation holding company that oversees Malaysia Airlines and several related aviation and travel businesses.
  • E. Malindo Air
    Malindo Air is a Malaysian hybrid full-service and low-cost airline that became the first operator of the Boeing 737 MAX 8.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d688f881909c85104a62e09d8a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62af90758819088999d98d270011a completed April 20, 2026, 1:32 p.m.
Created at: April 10, 2026, 1:37 p.m.