Triple

T2686097
Position Surface form Disambiguated ID Type / Status
Subject Sabah E57487 entity
Predicate contains P35 FINISHED
Object Keningau
Keningau is a major inland town and administrative district in the interior region of the Malaysian state of Sabah.
E288600 NE FINISHED

How this triple was built (4 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: Keningau | Statement: [Sabah, contains, Keningau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keningau
Context triple: [Sabah, contains, Keningau]
  • A. Ketapang
    Ketapang is a key ferry port town in East Java, Indonesia, serving as a primary gateway for sea crossings between Java and Bali.
  • B. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • C. Labuan
    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.
  • D. Labuan
    Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
  • E. Kuala Krai
    Kuala Krai is a town and district capital in the interior of Kelantan, Malaysia, known as a regional administrative and commercial center along the Kelantan River.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Keningau
Triple: [Sabah, contains, Keningau]
Generated description
Keningau is a major inland town and administrative district in the interior region of the Malaysian state of Sabah.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Keningau
Target entity description: Keningau is a major inland town and administrative district in the interior region of the Malaysian state of Sabah.
  • A. Ketapang
    Ketapang is a key ferry port town in East Java, Indonesia, serving as a primary gateway for sea crossings between Java and Bali.
  • B. Padang Besar
    Padang Besar is a border town in northern Malaysia known as a key land gateway and trading hub between Malaysia and Thailand.
  • C. Labuan
    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.
  • D. Labuan
    Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
  • E. Kuala Krai
    Kuala Krai is a town and district capital in the interior of Kelantan, Malaysia, known as a regional administrative and commercial center along the Kelantan River.
  • F. None of above. chosen

Provenance (5 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9ef2fe0819082bbe746ca682a7e completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afa07228088190bb4942b3a25c938b completed March 10, 2026, 4:39 a.m.
NEDg Description generation batch_69afa0ff9c10819096d06ead6dc87d04 completed March 10, 2026, 4:41 a.m.
NED2 Entity disambiguation (via description) batch_69afa1e4ffb08190a6d96665ee566ea7 completed March 10, 2026, 4:45 a.m.
Created at: March 6, 2026, 9:54 p.m.