Triple

T6118043
Position Surface form Disambiguated ID Type / Status
Subject Tsonga people E136409 entity
Predicate ethnonym P4709 FINISHED
Object Tsonga E70172 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: Tsonga | Statement: [Tsonga people, ethnonym, Tsonga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tsonga
Context triple: [Tsonga people, ethnonym, Tsonga]
  • A. Tsonga chosen
    Tsonga is a Bantu language spoken primarily in southern Africa, especially in Mozambique and South Africa, by the Tsonga (Xitsonga) people.
  • B. Marakwet
    Marakwet is a Southern Nilotic language spoken primarily by the Marakwet people of Kenya’s Rift Valley region.
  • C. Chambeali
    Chambeali is an Indo-Aryan language spoken primarily in the Chamba region of Himachal Pradesh in northern India.
  • D. Mbanderu
    Mbanderu is a subgroup of the Herero people with its own distinct dialect and cultural traditions, primarily found in Namibia and Botswana.
  • E. Mañegu
    Mañegu is a dialect of the Fala language spoken in the border region between Spain and Portugal, known for preserving distinctive features of Galician-Portuguese.
  • 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_69c0089f851c81909e5e189a617dcff6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bec9b8c8190b3268b0ba952aae6 completed March 22, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1256ddb38819095f582b6468db407 completed March 23, 2026, 11:35 a.m.
Created at: March 22, 2026, 4:14 p.m.