Triple

T17104117
Position Surface form Disambiguated ID Type / Status
Subject Port of Teluk Bayur E415053 entity
Predicate operatedBy P86 FINISHED
Object PT Pelabuhan Indonesia II E889174 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: PT Pelabuhan Indonesia II | Statement: [Port of Teluk Bayur, operatedBy, PT Pelabuhan Indonesia II]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PT Pelabuhan Indonesia II
Context triple: [Port of Teluk Bayur, operatedBy, PT Pelabuhan Indonesia II]
  • A. Pelindo II chosen
    Pelindo II is an Indonesian state-owned port management company responsible for operating and developing major seaports across western Indonesia.
  • B. Pelindo III
    Pelindo III is an Indonesian state-owned port management company that operates and develops several key seaports across central and eastern Indonesia.
  • C. Pelindo IV
    Pelindo IV is an Indonesian state-owned port operator responsible for managing and developing seaports across the eastern region of Indonesia.
  • D. Pelindo I
    Pelindo I is an Indonesian state-owned port operator responsible for managing and developing several key ports in the western region of Indonesia.
  • E. PT PAL Indonesia
    PT PAL Indonesia is a state-owned Indonesian shipbuilding company known for constructing naval and commercial vessels, including modern landing platform docks for regional and international clients.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2591a881909c5f4f7db47f4d6c completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139ffbe808190a24e827331ee4a6c completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:35 a.m.