Triple
T22933966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobaku |
E569523
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | variety of the Uma language |
C47038
|
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 the Uma language Context triple: [Tobaku, instanceOf, variety of the Uma language]
-
A.
variety of Kunama language
A variety of Kunama language is a distinct regional or social form of the Kunama language characterized by unique phonological, lexical, or grammatical features within the broader Kunama-speaking community.
-
B.
Yana language variety
Yana language variety refers to any of the related but distinct forms of the Yana language traditionally spoken by the Yana people of northern California, encompassing dialectal differences in phonology, vocabulary, and grammar.
-
C.
Amuzgo language variety
An Amuzgo language variety is a specific regional or social form of the Amuzgo language, distinguished by its unique phonological, lexical, and grammatical features within the broader Amuzgo linguistic continuum.
-
D.
Luri language variety
A Luri language variety is a specific regional or social form of the Luri language, distinguished by its own characteristic phonological, lexical, and grammatical features within the broader continuum of Southwestern Iranian dialects.
-
E.
variety of the Guna language
A variety of the Guna language is a distinct regional or social form of Guna characterized by systematic differences in pronunciation, vocabulary, and grammar while remaining mutually intelligible with other Guna 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
Created at: April 17, 2026, 3:44 p.m.