Triple
T1012643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiunguja |
E21856
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | variety of Swahili |
C5703
|
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: variety of Swahili Context triple: [Kiunguja, instanceOf, variety of Swahili]
-
A.
variety of Arabic
A variety of Arabic is a distinct form of the Arabic language, characterized by its own phonological, lexical, and grammatical features, typically associated with a particular region, community, or social context.
-
B.
variety of Latin
A variety of Latin is a distinct form or dialect of the Latin language characterized by specific historical period, geographic region, social group, or functional use.
-
C.
variety of the Spanish language
A variety of the Spanish language is a distinct form of Spanish characterized by specific phonological, grammatical, lexical, and pragmatic features associated with a particular geographic region, social group, or communicative context.
-
D.
variety of Mandarin Chinese
A variety of Mandarin Chinese is a regional or social form of the Mandarin language distinguished by its phonological, lexical, and sometimes grammatical features while remaining mutually intelligible with other Mandarin forms.
-
E.
variety of the Greek language
A variety of the Greek language is a distinct form or dialect of Greek, characterized by specific phonological, grammatical, lexical, and pragmatic features used by a particular community or in a particular context.
- F. None of above. chosen
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.