Triple
T7268080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanaga River |
E161028
|
entity |
| Predicate | roleInEnergySector |
P8439
|
FINISHED |
| Object | backbone of Cameroon hydropower potential |
—
|
LITERAL 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: backbone of Cameroon hydropower potential | Statement: [Sanaga River, roleInEnergySector, backbone of Cameroon hydropower potential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInEnergySector Context triple: [Sanaga River, roleInEnergySector, backbone of Cameroon hydropower potential]
-
A.
roleInIndustry
chosen
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
-
B.
hasOccupationSector
Indicates that an entity’s occupation belongs to or is categorized within a particular economic or professional sector.
-
C.
roleInPowerStation
Indicates that one entity holds a specific functional role or responsibility within the operation or management of a power station.
-
D.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
E.
roleInFinance
Indicates that an entity holds a specific function, responsibility, or position within a financial context, system, or transaction.
- F. None of above.
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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb088dac8190b353f6ea3d686025 |
completed | March 27, 2026, 8:39 p.m. |
| PD | Predicate disambiguation | batch_69c6e76876608190ac4652bc7153302e |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:58 p.m.