Triple
T20325439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luba |
E492319
|
entity |
| Predicate | hasSubgroups |
P2605
|
FINISHED |
| Object | Luba-Kasai |
—
|
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: Luba-Kasai | Statement: [Luba, hasSubgroups, Luba-Kasai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luba-Kasai Context triple: [Luba, hasSubgroups, Luba-Kasai]
-
A.
Luba-Kasai
chosen
Luba-Kasai is a Bantu language spoken primarily in the Kasai region of the Democratic Republic of the Congo by the Luba people.
-
B.
Kongolo
Kongolo is a town in the Tanganyika Province of the Democratic Republic of the Congo, situated along the Lukuga River and serving as a local transport and trading hub.
-
C.
Kongō
Kongō was a Japanese Kongō-class fast battleship that served prominently in the Imperial Japanese Navy during World War II.
-
D.
Katanga
Katanga is a mineral-rich region in the southeastern part of the Democratic Republic of the Congo, historically known for its attempted secession in the early 1960s and significant role in the country’s political conflicts.
-
E.
Middle Congo
Middle Congo was a former French colonial territory in Central Africa that later became the independent Republic of the Congo (Congo-Brazzaville).
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778f20288190b1862d6be61bfb67 |
completed | April 20, 2026, 6:59 p.m. |
Created at: April 16, 2026, 11:21 a.m.