Triple
T22955788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Musanze |
E570750
|
entity |
| Predicate | languageUsed |
P238
|
FINISHED |
| Object | Kinyarwanda |
—
|
NE NERFINISHED |
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 | Statement: [Musanze, languageUsed, Kinyarwanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kinyarwanda Context triple: [Musanze, languageUsed, Kinyarwanda]
-
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.
Kinyarwanda–Rundi languages
The Kinyarwanda–Rundi languages are a closely related cluster of Bantu languages spoken primarily in Rwanda and Burundi, including Kinyarwanda and Kirundi.
-
D.
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.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f09de48190b55913570c965412 |
completed | April 29, 2026, 3:58 a.m. |
Created at: April 17, 2026, 3:47 p.m.