Triple

T15324124
Position Surface form Disambiguated ID Type / Status
Subject Brunei Bay E366365 entity
Predicate borderedBy P224 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: [Brunei Bay, borderedBy, Labuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Labuan
Context triple: [Brunei Bay, borderedBy, 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_69d85a121520819093dcce999fdefe1a completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd5ce0c819093c9a14de549dff6 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8aaef608190bd3ec9fdd215afbb completed May 9, 2026, 9:04 a.m.
Created at: April 10, 2026, 3:16 a.m.