Triple
T22908945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ebolowa |
E568529
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Mvila Department |
—
|
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: Mvila Department | Statement: [Ebolowa, partOf, Mvila Department]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mvila Department Context triple: [Ebolowa, partOf, Mvila Department]
-
A.
Mvila Department
chosen
Mvila Department is an administrative division in southern Cameroon, located in the South Region and known for its capital, Ebolowa.
-
B.
Menoua Department
Menoua Department is an administrative division in western Cameroon known for its highland landscapes, agricultural activities, and culturally diverse communities.
-
C.
Biedma Department
Biedma Department is an administrative division in Chubut Province, Argentina, known for encompassing the Valdés Peninsula and its important marine wildlife reserves.
-
D.
Ndé Department
Ndé Department is an administrative division in western Cameroon known for its predominantly rural communities and agricultural activities.
-
E.
Lékoumou Department
Lékoumou Department is an administrative region in the Republic of the Congo located in the southern part of the country.
- 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_69e2458cd9e48190943ad2e34485d939 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18072986881909eefb317ced5a145 |
completed | April 29, 2026, 3:52 a.m. |
Created at: April 17, 2026, 3:42 p.m.