Triple
T30960556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takas |
E788800
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | variety of Mwaghavul language |
C58813
|
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 Mwaghavul language Context triple: [Takas, instanceOf, variety of Mwaghavul language]
-
A.
variety of Wapishana language
A variety of the Wapishana language is a distinct regional or social form of Wapishana, characterized by unique phonological, lexical, or grammatical features while remaining mutually intelligible with other forms.
-
B.
Makhuwa language variety
A Makhuwa language variety is a specific regional or social form of the Makhuwa Bantu language, distinguished by its own phonological, lexical, or grammatical features within the broader Makhuwa linguistic continuum.
-
C.
variety of Swahili
A variety of Swahili is a distinct form of the Swahili language characterized by specific regional, social, or functional linguistic features in its phonology, grammar, and vocabulary.
-
D.
variety of Malagasy language
A variety of Malagasy language is a distinct regional or social form of Malagasy characterized by unique phonological, lexical, and grammatical features while remaining mutually intelligible to varying degrees with other Malagasy forms.
-
E.
variety of the Uma language
A variety of the Uma language is a distinct regional or social form of Uma characterized by systematic differences in pronunciation, vocabulary, or grammar while remaining mutually intelligible with other forms.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
Created at: April 29, 2026, 8:54 p.m.