Triple

T418232
Position Surface form Disambiguated ID Type / Status
Subject Gauteng E8041 entity
Predicate officialLanguage P236 FINISHED
Object Xhosa E11008 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: Xhosa | Statement: [Gauteng, officialLanguage, Xhosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Xhosa
Context triple: [Gauteng, officialLanguage, Xhosa]
  • A. Xhosa chosen
    Xhosa is a Bantu language of South Africa, known for its distinctive click consonants and as one of the country’s major official languages.
  • B. Xitsonga
    Xitsonga is a Bantu language spoken primarily by the Tsonga people in southern Africa, notably in South Africa, Mozambique, and Zimbabwe.
  • C. Tshivenda
    Tshivenda is a Bantu language spoken primarily by the Venda people in northern South Africa and neighboring regions.
  • D. Zulu
    Zulu is a Bantu language of the Nguni group spoken primarily in South Africa and widely influential in the country’s culture and other local languages.
  • E. Sesotho
    Sesotho is a Southern Bantu language spoken primarily in Lesotho and South Africa, where it holds official status and serves as a major medium of communication and cultural identity.
  • 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_69a2e7f1d1bc81909cf2dc9754a3c334 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ee9059248190ba901680431914b5 completed Feb. 28, 2026, 1:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69a42543e3ec81908a56075495b1279f completed March 1, 2026, 11:38 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.