Triple

T8670944
Position Surface form Disambiguated ID Type / Status
Subject Sultan Abdul Halim Airport E205793 entity
Predicate hasHubAirline P423 FINISHED
Object Malaysia Airlines E13188 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: Malaysia Airlines | Statement: [Sultan Abdul Halim Airport, hasHubAirline, Malaysia Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malaysia Airlines
Context triple: [Sultan Abdul Halim Airport, hasHubAirline, Malaysia Airlines]
  • A. Malaysia Airlines chosen
    Malaysia Airlines is the flag carrier of Malaysia, operating international and domestic flights across Asia, Europe, and other regions from its main hub in Kuala Lumpur.
  • B. 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.
  • C. 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.
  • D. Lion Air
    Lion Air is a major Indonesian low-cost airline operating extensive domestic and regional routes across Southeast Asia.
  • E. Mandala Airlines
    Mandala Airlines was an Indonesian airline that operated domestic and regional flights before ceasing operations in the early 2010s.
  • 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_69ca83529a9c8190b5c075b4f14636ed completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4918e3a88190b3c49043211840fd completed March 31, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecd2b996481908da33fbd95494376 completed April 2, 2026, 8:10 p.m.
Created at: March 30, 2026, 6:31 p.m.