Triple

T16058547
Position Surface form Disambiguated ID Type / Status
Subject MASwings Sdn Bhd E389545 entity
Predicate regionServed P82 FINISHED
Object Labuan E47879 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 | Statement: [MASwings Sdn Bhd, regionServed, Labuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Labuan
Context triple: [MASwings Sdn Bhd, regionServed, Labuan]
  • A. Labuan chosen
    Labuan is a federal territory of Malaysia comprising a main island and several smaller ones, known as an offshore financial center and duty-free port off the coast of Borneo.
  • B. Labuan
    Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
  • C. Tawau
    Tawau is a coastal town and major economic hub in southeastern Sabah, Malaysia, known for its port, agriculture, and proximity to Indonesia.
  • D. Tanjung Selor
    Tanjung Selor is an administrative town in Indonesian Borneo that serves as the governmental and economic center of North Kalimantan province.
  • E. Kota Belud
    Kota Belud is a town and district in Sabah, Malaysia, known for its vibrant Bajau culture, weekly tamu (market), and scenic coastal and rural landscapes.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837634248190a99cc454ad1e99e0 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe678fc8190b36737a9cd29691c completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.