Triple
T3354541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cahora Bassa Dam |
E70573
|
entity |
| Predicate | reservoirArea |
P35437
|
FINISHED |
| Object | large surface area relative to African reservoirs |
—
|
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: large surface area relative to African reservoirs | Statement: [Cahora Bassa Dam, reservoirArea, large surface area relative to African reservoirs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reservoirArea Context triple: [Cahora Bassa Dam, reservoirArea, large surface area relative to African reservoirs]
-
A.
reservoirSurfaceArea
chosen
Indicates the total area covered by the surface of a reservoir.
-
B.
lakeArea
Indicates the surface area measurement of a lake.
-
C.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
D.
reservoir
Indicates that one entity serves as a storage or containment source (often for a resource) that can supply or affect another entity.
-
E.
reservoirTotalCapacity
Indicates the maximum volume of water that a reservoir is designed to hold when full.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb24036848190bac779d17dfdce3b |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42fbe7c8190b9f185b5ab985f17 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.