Triple

T21588043
Position Surface form Disambiguated ID Type / Status
Subject Kisukuma language E532703 entity
Predicate hasAlternativeName P39 FINISHED
Object Sukuma language 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: Sukuma language | Statement: [Kisukuma language, hasAlternativeName, Sukuma language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sukuma language
Context triple: [Kisukuma language, hasAlternativeName, Sukuma language]
  • A. Sukuma language chosen
    The Sukuma language is a Bantu language spoken primarily by the Sukuma people in northwestern Tanzania.
  • B. Kisukuma language
    Kisukuma is a major Bantu language spoken primarily by the Sukuma people in northwestern Tanzania.
  • C. Nyaturu language
    The Nyaturu language is a Bantu language spoken primarily by the Nyaturu people in central Tanzania.
  • D. Lusoga language
    The Lusoga language is a Bantu language spoken primarily by the Basoga people in eastern Uganda.
  • E. Nyemba language
    The Nyemba language is a Bantu language spoken primarily by the Nyemba (Nyaneka-Nkhumbi) people of southwestern Angola.
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb621ab88190a33a943424ffb306 completed April 27, 2026, 4:51 a.m.
Created at: April 16, 2026, 6:31 p.m.