Triple
T7164890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lusaka Province |
E167040
|
entity |
| Predicate | language |
P15
|
FINISHED |
| Object | Nyanja |
E136466
|
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: Nyanja | Statement: [Lusaka Province, language, Nyanja]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nyanja Context triple: [Lusaka Province, language, Nyanja]
-
A.
Nyanja
chosen
Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
-
B.
Kasindi
Kasindi is a border town in eastern Democratic Republic of the Congo, located near Uganda and serving as an important regional trade and transport hub.
-
C.
Kigoma
Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
-
D.
Kalangala
Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
-
E.
Nyamwezi
Nyamwezi is a Bantu language spoken primarily in northwestern Tanzania by the Nyamwezi people.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e83168a08190937ff46797d94f3e |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adcc145c8190ba65831ed891a225 |
completed | March 28, 2026, 10:30 a.m. |
Created at: March 27, 2026, 2:47 p.m.