Triple

T15219802
Position Surface form Disambiguated ID Type / Status
Subject Ndau people E363735 entity
Predicate languageGroup P3349 FINISHED
Object Shona languages 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 languages | Statement: [Ndau people, languageGroup, Shona languages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shona languages
Context triple: [Ndau people, languageGroup, Shona languages]
  • 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. Silozi language
    The Silozi language is a Bantu language spoken primarily by the Lozi people in western Zambia and surrounding regions.
  • C. Tumbuka
    Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and Tanzania.
  • D. Mambwe-Lungu language
    The Mambwe-Lungu language is a Bantu language spoken primarily in parts of Zambia and Tanzania by the Mambwe and closely related Lungu communities.
  • E. Tswa–Ronga languages
    The Tswa–Ronga languages are a closely related group of Bantu languages spoken primarily in southern Africa, including varieties such as Tsonga and Ronga.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007709d3881908384f0fe1e0218d0 completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed345d58c81908a8fd182c0fe7c15 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.