Triple
T1012642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiunguja |
E21856
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Swahili dialect |
C3817
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: Swahili dialect Context triple: [Kiunguja, instanceOf, Swahili dialect]
-
A.
Bantu language
chosen
A Bantu language is a member of a large branch of the Niger-Congo language family, spoken primarily in central, eastern, and southern Africa, characterized by noun class systems and agglutinative morphology.
-
B.
Chadic language
A Chadic language is any member of a branch of the Afroasiatic language family spoken primarily in parts of Nigeria, Niger, Chad, Cameroon, and neighboring regions, characterized by diverse phonological systems and complex verb morphology.
-
C.
Chibchan language
A Chibchan language is a member of a family of indigenous languages spoken primarily in Central America and northern South America, characterized by shared grammatical and phonological features reflecting a common ancestral origin.
-
D.
Quechuan language
A Quechuan language is any member of a family of indigenous languages of the Andes, primarily spoken in Peru, Bolivia, Ecuador, Colombia, and Argentina, that share common grammatical structures and vocabulary derived from a Proto-Quechuan ancestor.
-
E.
lingua franca
A lingua franca is a language systematically used to make communication possible between people who do not share a native language, often for trade, diplomacy, or other practical purposes.
- F. None of above.
Provenance (1 batch)
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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
Created at: March 1, 2026, 7:41 p.m.