Triple
T18729196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diabaly |
E457985
|
entity |
| Predicate | languageSpoken |
P151
|
FINISHED |
| Object | Bambara |
—
|
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: Bambara | Statement: [Diabaly, languageSpoken, Bambara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bambara Context triple: [Diabaly, languageSpoken, Bambara]
-
A.
Bambara
chosen
Bambara is a major Mande language widely spoken in Mali and neighboring West African countries, serving as a key lingua franca in the region.
-
B.
Dioula
Dioula is a Mande language of West Africa, widely used as a trade and lingua franca language in countries like Burkina Faso, Côte d’Ivoire, and Mali.
-
C.
Dosso Zarma
Dosso Zarma is a major regional variety of the Zarma language spoken primarily around the Dosso area of Niger.
-
D.
Mandingo
Mandingo is a controversial 1975 American film set on a Southern slave plantation, known for its graphic depiction of slavery, racism, and sexual exploitation.
-
E.
Mandingo
Mandingo is a Mande language spoken primarily by the Mandinka people across several West African countries, including Mali, Senegal, Gambia, and Guinea.
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d7660488190b4f70db963d05ef6 |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:50 a.m.