Triple
T23476693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lozi language |
E570282
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Silozi |
—
|
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: Silozi | Statement: [Lozi language, hasAlternativeName, Silozi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Silozi Context triple: [Lozi language, hasAlternativeName, Silozi]
-
A.
Silozi
chosen
Silozi is a Bantu language spoken primarily by the Lozi people of western Zambia and surrounding regions.
-
B.
Mumbwa
Mumbwa is a town in central Zambia known as an agricultural and mining hub west of the capital, Lusaka.
-
C.
Lusambo
Lusambo is a town in the Democratic Republic of the Congo that once served as an important colonial and regional administrative center in the Kasai area.
-
D.
Ntshona
Ntshona is the surname of South African actor and playwright Winston Ntshona, known for his influential work in anti-apartheid theatre.
-
E.
Mkushi
Mkushi is a farming and trading town in Zambia known for its commercial agriculture, particularly large-scale commercial farming.
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a74cf57081909d2b90a806d68c08 |
completed | April 29, 2026, 6:38 a.m. |
Created at: April 17, 2026, 6:01 p.m.