Triple
T1030770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimvita |
E22244
|
entity |
| Predicate | hasDialectStatus |
P24201
|
FINISHED |
| Object | major coastal dialect of Swahili |
—
|
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: major coastal dialect of Swahili | Statement: [Kimvita, hasDialectStatus, major coastal dialect of Swahili]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialectStatus Context triple: [Kimvita, hasDialectStatus, major coastal dialect of Swahili]
-
A.
hasDialects
Indicates that an entity (typically a language) possesses one or more distinct dialectal varieties.
-
B.
affectsDialect
Indicates that one entity influences or changes the dialect used or spoken by another entity.
-
C.
hasMajorDialectGroup
Indicates that an entity (typically a language) is associated with a primary or major dialect group to which it belongs.
-
D.
hasUnicodeStatus
Indicates that a given entity has a particular Unicode-related classification or status (such as assigned, reserved, deprecated, or noncharacter) within the Unicode standard.
-
E.
hasDatabase
Indicates that an entity possesses, uses, or is associated with a specific database.
- F. None of above. chosen
Provenance (4 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b95d35888190a20593a278175df7 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b7276180819085c6b23501a6a6e0 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b95bb5908190ad1d5f5e0d8f664d |
completed | March 1, 2026, 10:10 p.m. |
Created at: March 1, 2026, 7:41 p.m.