Triple

T16405568
Position Surface form Disambiguated ID Type / Status
Subject Malaysian airport network E398415 entity
Predicate hasComponent P35 FINISHED
Object Labuan Airport E241951 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: Labuan Airport | Statement: [Malaysian airport network, hasComponent, Labuan Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Labuan Airport
Context triple: [Malaysian airport network, hasComponent, Labuan Airport]
  • A. Labuan Airport chosen
    Labuan Airport is a public airport serving the island and federal territory of Labuan in Malaysia, handling domestic flights and some regional connections.
  • B. Tawau Airport
    Tawau Airport is a public airport in Sabah, Malaysia, serving the town of Tawau and acting as a key gateway to the southeastern region of Borneo.
  • C. Keningau Airport
    Keningau Airport is a small regional airfield serving the town of Keningau in the interior of Sabah, Malaysia.
  • D. Mutiara Airport
    Mutiara Airport is a public airport in Palu, Central Sulawesi, Indonesia, serving as the main air gateway to the region.
  • E. Kualanamu International Airport
    Kualanamu International Airport is a major international airport in North Sumatra, Indonesia, serving the city of Medan as one of the country’s primary air transport hubs.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e327d2b4e48190b7153f198639e9cd completed April 18, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00aae394d48190aca8e6f5e1cc781f completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:09 a.m.