Triple
T16418159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mara Region |
E398740
|
entity |
| Predicate | ethnicGroup |
P194
|
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: [Mara Region, ethnicGroup, Sukuma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sukuma Context triple: [Mara Region, ethnicGroup, 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.
Cuemba River
The Cuemba River is a watercourse in Angola that flows through Malanje Province, contributing to the region’s local hydrology and ecosystems.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328798a488190a5fad01c3c95584c |
completed | April 18, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00679a900c8190aeb7a273943bf553 |
completed | May 10, 2026, 11:10 a.m. |
Created at: April 10, 2026, 5:09 a.m.