Triple

T2662905
Position Surface form Disambiguated ID Type / Status
Subject Benue–Congo languages E54765 entity
Predicate hasNotableLanguage P7390 FINISHED
Object Shona language E28785 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: Shona language | Statement: [Benue–Congo languages, hasNotableLanguage, Shona language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shona language
Context triple: [Benue–Congo languages, hasNotableLanguage, Shona language]
  • A. Shona chosen
    Shona is a major Bantu language of Zimbabwe, widely spoken by the Shona people and used in education, media, and government.
  • B. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • C. Tshivenda
    Tshivenda is a Bantu language spoken primarily by the Venda people in northern South Africa and neighboring regions.
  • D. Chichewa
    Chichewa is a major Bantu language spoken primarily in Malawi and neighboring countries, serving as a national and widely used lingua franca in the region.
  • E. Xitsonga
    Xitsonga is a Bantu language spoken primarily by the Tsonga people in southern Africa, notably in South Africa, Mozambique, and Zimbabwe.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd96b9f1c8190a8a9460ca88a9aaf completed March 7, 2026, 7:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98dc36d8819086fc739c324f0761 completed March 10, 2026, 4:06 a.m.
Created at: March 6, 2026, 9:53 p.m.