Triple
T5548869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narrow Bantu |
E145475
|
entity |
| Predicate | includes |
P1393
|
FINISHED |
| Object | Kinyarwanda language |
E65621
|
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: Kinyarwanda language | Statement: [Narrow Bantu, includes, Kinyarwanda language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinyarwanda language Context triple: [Narrow Bantu, includes, Kinyarwanda language]
-
A.
Kinyarwanda
chosen
Kinyarwanda is a Bantu language spoken primarily in Rwanda, where it serves as a national and widely used lingua franca.
-
B.
Kirundi
Kirundi is a Bantu language primarily spoken in Burundi and neighboring regions of East Africa.
-
C.
Kitwe
Kitwe is a major mining and industrial city in Zambia’s Copperbelt Province, known as one of the country’s largest urban and economic centers.
-
D.
Kikongo
Kikongo is a Bantu language widely spoken in Central Africa, particularly in the western regions of the Democratic Republic of the Congo and neighboring countries.
-
E.
Nyamwezi language
The Nyamwezi language is a Bantu language spoken primarily by the Nyamwezi people of western-central Tanzania.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe143ec8190bb67d2530c92a419 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0282dd7408190ad762fca9ff5e04b |
completed | March 22, 2026, 5:34 p.m. |
Created at: March 22, 2026, 3:35 p.m.