Triple
T8309673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagera Region |
E194558
|
entity |
| Predicate | hasEthnicGroup |
P1898
|
FINISHED |
| Object | Sukuma |
E617029
|
NE 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: Sukuma | Statement: [Kagera Region, hasEthnicGroup, Sukuma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sukuma Context triple: [Kagera Region, hasEthnicGroup, Sukuma]
-
A.
Sukuma
chosen
Sukuma is a major Bantu language spoken primarily by the Sukuma people in northern Tanzania.
-
B.
Usutu River
The Usutu River is a major river in southern Africa that flows through South Africa, Eswatini, and Mozambique before emptying into the Indian Ocean.
-
C.
Unzha River
The Unzha River is a significant waterway in central Russia that flows through Kostroma and neighboring regions before joining the Volga River.
-
D.
Ulanga River
The Ulanga River is a fictional East African waterway famously depicted as the treacherous river route navigated in C.S. Forester’s novel and the classic film "The African Queen."
-
E.
Ngadda River
The Ngadda River is a waterway in northeastern Nigeria that flows through the city of Maiduguri and contributes to the region’s drainage into Lake Chad.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca82e613e88190bf8139669bbd0d53 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f2d2c30819095075940479b75a7 |
completed | March 31, 2026, 8 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce026bef88819097459cb96f7b44af |
completed | April 2, 2026, 5:45 a.m. |
Created at: March 30, 2026, 5:54 p.m.