Triple

T7655174
Position Surface form Disambiguated ID Type / Status
Subject Sarawak Malay E173361 entity
Predicate hasRegion P285 FINISHED
Object Sibu E361159 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: Sibu | Statement: [Sarawak Malay, hasRegion, Sibu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sibu
Context triple: [Sarawak Malay, hasRegion, Sibu]
  • A. Sibu chosen
    Sibu is a major town in the central region of Sarawak, Malaysia, known as a commercial and transportation hub on the island of Borneo.
  • B. Sibutu
    Sibutu is a small but strategically located island in the southern Philippines near the maritime border with Malaysia, known for its role in regional sea routes and its predominantly Muslim population.
  • C. Oshikwambi
    Oshikwambi is a regional dialect of the Oshiwambo language spoken by the Kwambi people in northern Namibia.
  • D. Bongwe
    Bongwe is a dialect of the Duala language spoken by the Duala people of Cameroon.
  • E. Kisoro
    Kisoro is a small town in southwestern Uganda known as a gateway to gorilla trekking and the nearby Bwindi Impenetrable and Mgahinga Gorilla National Parks.
  • 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_69c6995473348190a4f41d110d619a18 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018ea3688190907c3ac7d25e3da6 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8ac925a6c8190aa7a4fe4f580d14f completed March 29, 2026, 4:37 a.m.
Created at: March 27, 2026, 3:59 p.m.