Triple

T12789829
Position Surface form Disambiguated ID Type / Status
Subject Muanda Territory E305728 entity
Predicate hasNationalLanguage P17042 FINISHED
Object Tshiluba E54338 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: Tshiluba | Statement: [Muanda Territory, hasNationalLanguage, Tshiluba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tshiluba
Context triple: [Muanda Territory, hasNationalLanguage, Tshiluba]
  • A. Tshiluba chosen
    Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
  • B. Tshimanda
    Tshimanda is a regional dialect of the Tshivenda language spoken by a specific community of Venda people in South Africa.
  • C. Lubemba
    Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
  • D. Masisi
    Masisi is a town in the eastern Democratic Republic of the Congo, situated in the conflict-affected, mineral-rich highlands of North Kivu Province.
  • E. Luba
    Luba is a coastal town and important port on the southern part of Bioko Island in Equatorial Guinea.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6a61f48190972e241e70bc392c completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8c75a048190aee92e50017c214e completed May 3, 2026, 2:53 a.m.
Created at: April 9, 2026, 5:30 p.m.