Triple

T13475246
Position Surface form Disambiguated ID Type / Status
Subject KUL E318232 entity
Predicate servesAsFocusCityFor P1655 FINISHED
Object Batik Air Malaysia E553770 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: Batik Air Malaysia | Statement: [KUL, servesAsFocusCityFor, Batik Air Malaysia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Batik Air Malaysia
Context triple: [KUL, servesAsFocusCityFor, Batik Air Malaysia]
  • A. Batik Air
    Batik Air is an Indonesian full-service airline operating domestic and regional flights as part of the Lion Air Group.
  • B. Malindo Air chosen
    Malindo Air is a Malaysian hybrid full-service and low-cost airline that became the first operator of the Boeing 737 MAX 8.
  • C. Belau Air
    Belau Air is a small regional airline based in Palau that operates domestic and nearby international flights, primarily serving local island communities.
  • D. AirAsia
    AirAsia is a Malaysian low-cost airline known for its extensive network of domestic and international routes across Asia and beyond.
  • 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_69d806b6bfec819089222715b2e86c8e completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf2551b48190a074fd256791742d completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f7fcab0819091146d54d56f08d7 completed May 3, 2026, 5:01 p.m.
Created at: April 9, 2026, 9:42 p.m.