Triple
T5794827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tshimanda |
E128482
|
entity |
| Predicate | relatedDialectOf |
P10003
|
FINISHED |
| Object | Venda language |
—
|
LITERAL FINISHED |
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: Venda language | Statement: [Tshimanda, relatedDialectOf, Venda language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedDialectOf Context triple: [Tshimanda, relatedDialectOf, Venda language]
-
A.
majorDialectOf
Indicates that one dialect is the primary or most prominent dialect associated with a particular language or region.
-
B.
hasDialectContinuumWith
Indicates that two languages or dialects are part of a continuous chain of mutually intelligible varieties, without a clear boundary separating them.
-
C.
notableDialect
Indicates that an entity is recognized for having a distinct or noteworthy dialect associated with it.
-
D.
linguisticallyRelatedTo
chosen
Indicates that two entities are connected through a linguistic relationship, such as sharing a common language, origin, structure, or other language-based association.
-
E.
focusesOnDialect
Indicates that the subject’s attention, work, or activity is specifically directed toward a particular dialect or set of dialects.
- F. None of above.
Provenance (3 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1304588190b59a18fb7b70a60f |
completed | March 22, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.