Triple

T21803942
Position Surface form Disambiguated ID Type / Status
Subject South African newspapers E538302 entity
Predicate language P15 FINISHED
Object Tshivenda NE NERFINISHED

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: Tshivenda | Statement: [South African newspapers, language, Tshivenda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tshivenda
Context triple: [South African newspapers, language, Tshivenda]
  • A. Tshivenda chosen
    Tshivenda is a Bantu language spoken primarily by the Venda people in northern South Africa and neighboring regions.
  • B. Siswati
    Siswati is a Bantu language of the Nguni group spoken primarily in Eswatini and South Africa, where it holds official status.
  • C. Xitsonga
    Xitsonga is a Bantu language spoken primarily by the Tsonga people in southern Africa, notably in South Africa, Mozambique, and Zimbabwe.
  • 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. Zulu
    Zulu is a 1964 British war film depicting the Battle of Rorke's Drift during the Anglo-Zulu War, noted for being one of Michael Caine's early breakthrough roles.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c4733f4081909a86622e7e6d15d2 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0780126e88190a93dd8d0519eb8fc completed April 28, 2026, 9:04 a.m.
Created at: April 16, 2026, 6:53 p.m.