Triple
T12039990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bemba language |
E286634
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | Ichibemba |
E712127
|
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: Ichibemba | Statement: [Bemba language, alternativeName, Ichibemba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ichibemba Context triple: [Bemba language, alternativeName, Ichibemba]
-
A.
Enbilulu
Enbilulu is a Mesopotamian deity associated with irrigation, canals, and the management of rivers and agricultural waters.
-
B.
Lubemba
chosen
Lubemba is the traditional kingdom and cultural heartland of the Bemba people in what is now northern Zambia.
-
C.
Buhera
Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
-
D.
Biloela
Biloela is a rural town in Queensland, Australia, known as an agricultural and administrative centre for the surrounding Central Queensland region.
-
E.
Urambo
Urambo is a town and district headquarters in western Tanzania known historically for tobacco production and its location within the Tabora Region.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040c1a6c8190aea1388e82dd8f5a |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d9937a08190b2f606a1e55733b5 |
completed | May 1, 2026, 12:33 p.m. |
Created at: April 8, 2026, 9:47 p.m.