Triple
T2566132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kikongo |
E57354
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Kituba |
E51306
|
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: Kituba | Statement: [Kikongo, influenced, Kituba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kituba Context triple: [Kikongo, influenced, Kituba]
-
A.
Kituba
chosen
Kituba is a widely spoken Bantu-based creole language of Central Africa, serving as a major lingua franca in the Republic of the Congo and surrounding regions.
-
B.
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.
-
C.
Kichwa
Kichwa is a Quechuan indigenous language variety widely spoken by Andean communities in Ecuador and neighboring regions.
-
D.
Kimbundu
Kimbundu is a major Bantu language spoken primarily in northwestern Angola, especially around the capital Luanda, by the Ambundu people.
-
E.
Tumbuka
Tumbuka is a Bantu language spoken primarily in northern Malawi and parts of Zambia and 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_69ab4a4ef9008190a0e6d4422b9418b7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd35ef22c8190966612cc75f69eca |
completed | March 7, 2026, 7:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af83a4f6788190be268076838711df |
completed | March 10, 2026, 2:36 a.m. |
Created at: March 6, 2026, 9:48 p.m.