Triple

T6184794
Position Surface form Disambiguated ID Type / Status
Subject Kadazan Dusun language E138029 entity
Predicate hasDialects P4251 FINISHED
Object Bundu-Liwan
Bundu-Liwan is a major dialect of the Kadazan Dusun language spoken by indigenous communities in Sabah, Malaysia.
 E574305 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: Bundu-Liwan | Statement: [Kadazan Dusun language, hasDialects, Bundu-Liwan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bundu-Liwan
Context triple: [Kadazan Dusun language, hasDialects, Bundu-Liwan]
  • A. Lunda
    Lunda is a Bantu language spoken primarily by the Lunda people in parts of Zambia, Angola, and the Democratic Republic of the Congo.
  • B. Bashenga
    Bashenga is a legendary Wakandan warrior and the first Black Panther, revered as the founder of the Panther cult and an ancestor of T'Challa in Marvel Comics.
  • C. Chindau
    Chindau is a Bantu language spoken primarily by the Ndau people in parts of Mozambique and Zimbabwe.
  • D. Soshanguve
    Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
  • E. Itumbiara
    Itumbiara is a municipality in the Brazilian state of Goiás, known for its strategic location on the Paranaíba River and its role as a regional economic and transportation hub.
  • 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: Bundu-Liwan
Triple: [Kadazan Dusun language, hasDialects, Bundu-Liwan]
Generated description
Bundu-Liwan is a major dialect of the Kadazan Dusun language spoken by indigenous communities in Sabah, Malaysia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bundu-Liwan
Target entity description: Bundu-Liwan is a major dialect of the Kadazan Dusun language spoken by indigenous communities in Sabah, Malaysia.
  • A. Lunda
    Lunda is a Bantu language spoken primarily by the Lunda people in parts of Zambia, Angola, and the Democratic Republic of the Congo.
  • B. Bashenga
    Bashenga is a legendary Wakandan warrior and the first Black Panther, revered as the founder of the Panther cult and an ancestor of T'Challa in Marvel Comics.
  • C. Chindau
    Chindau is a Bantu language spoken primarily by the Ndau people in parts of Mozambique and Zimbabwe.
  • D. Soshanguve
    Soshanguve is a large township in the northern part of the Gauteng province of South Africa, known for its diverse population and proximity to Pretoria.
  • E. Itumbiara
    Itumbiara is a municipality in the Brazilian state of Goiás, known for its strategic location on the Paranaíba River and its role as a regional economic and transportation hub.
  • 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_69c008a8fd408190b7ec6e42934974a6 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c061020d148190ae2edf2b363f1e24 completed March 22, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141c6b5888190983bff620c7663cc completed March 23, 2026, 1:36 p.m.
NEDg Description generation batch_69c1472997d081909266b0e64fdbfe96 completed March 23, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_69c147b5214c819082c20480965842be completed March 23, 2026, 2:01 p.m.
Created at: March 22, 2026, 4:19 p.m.