Triple
T1012681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kiunguja |
E21856
|
entity |
| Predicate | regionStatus |
P23251
|
FINISHED |
| Object | prestige dialect of Swahili in Tanzania |
—
|
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: prestige dialect of Swahili in Tanzania | Statement: [Kiunguja, regionStatus, prestige dialect of Swahili in Tanzania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionStatus Context triple: [Kiunguja, regionStatus, prestige dialect of Swahili in Tanzania]
-
A.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
B.
territorialStatus
Indicates the legal or political condition of control, sovereignty, or jurisdiction that applies to a specific territory.
-
C.
regionException
Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
-
D.
statusInUnitedStates
Indicates the legal or official standing that an entity holds within the jurisdiction of the United States.
-
E.
stateRock
Indicates that an entity is in a solid, rock-like physical state or condition.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7be907c8190b5c6ea89257755a7 |
completed | March 1, 2026, 10:03 p.m. |
| PD | Predicate disambiguation | batch_69a4b72207c08190a3dbb2aa7acbbc71 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7bd3d50819091e6f1d2ffe4c7ee |
completed | March 1, 2026, 10:03 p.m. |
Created at: March 1, 2026, 7:41 p.m.