Triple
T23560089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badja Djola |
E579211
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Badja Djola |
—
|
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: Badja Djola | Statement: [Badja Djola, name, Badja Djola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badja Djola Context triple: [Badja Djola, name, Badja Djola]
-
A.
Badja Djola
chosen
Badja Djola was an American character actor known for his intense and memorable supporting roles in films and television from the 1970s through the 1990s.
-
B.
Baatonou
Baatonou refers to the Bariba people, a major ethnic group of northern Benin known for their historical kingdoms and distinct cultural traditions.
-
C.
Jola-Bandial
Jola-Bandial is a Niger-Congo language variety spoken by the Jola people of the Casamance region in southern Senegal.
-
D.
Langoué Baï
Langoué Baï is a renowned forest clearing in Gabon celebrated for its rich biodiversity and frequent gatherings of forest elephants and other wildlife.
-
E.
Mundemba
Mundemba is a town in southwestern Cameroon known as a gateway to the biodiverse Korup National Park.
- 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_69e245fe24588190888f3aec8407d8e3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af672db4819087dbff2c0dfadd7f |
completed | April 29, 2026, 7:12 a.m. |
Created at: April 17, 2026, 6:12 p.m.