Triple

T431483
Position Surface form Disambiguated ID Type / Status
Subject Malaysia E9722 entity
Predicate containsAdministrativeDivision P747 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: [Malaysia, containsAdministrativeDivision, Labuan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Labuan
Context triple: [Malaysia, containsAdministrativeDivision, 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. Penang
    Penang is a Malaysian state and island renowned for its multicultural heritage, historic George Town, and vibrant street food scene.
  • C. Bantia
    Bantia was an ancient Oscan-speaking city in southern Italy, notable for yielding important inscriptions that illuminate the Oscan language and Italic legal traditions.
  • D. Tanjung Perak
    Tanjung Perak is a major seaport in Surabaya, Indonesia, serving as one of the country’s principal maritime gateways for trade and passenger traffic.
  • E. Malacca
    Malacca is a historic Malaysian state on the southwest coast of the Malay Peninsula, renowned for its rich multicultural heritage and its former role as a major trading port.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f01be4108190b4c13346afd95a03 completed Feb. 28, 2026, 1:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69a447fa97ac8190b8a19ded2d0f520e completed March 1, 2026, 2:06 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.