Triple
T38187814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theewaterskloof Dam |
E1005366
|
entity |
| Predicate | rankInRegionByCapacity |
P128263
|
FINISHED |
| Object | one of the largest dams in the Western Cape |
—
|
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: one of the largest dams in the Western Cape | Statement: [Theewaterskloof Dam, rankInRegionByCapacity, one of the largest dams in the Western Cape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInRegionByCapacity Context triple: [Theewaterskloof Dam, rankInRegionByCapacity, one of the largest dams in the Western Cape]
-
A.
rankByCapacityInUS
Indicates the relative ordering of entities based on their capacity within the United States.
-
B.
rankByCapacityInAfrica
chosen
Indicates the relative ordering of entities based on their capacity within the context of Africa.
-
C.
capacityRank
Indicates the relative ordering of entities based on how much capacity (e.g., volume, throughput, or capability) they possess compared to others.
-
D.
rankInNorwayByCapacity
Indicates the position an entity holds in Norway when entities are ordered by their capacity, typically from highest to lowest.
-
E.
rankInSpainByCapacity
Indicates the position of an entity in the ordered list of entities in Spain when sorted by their capacity, from highest to lowest (or vice versa).
- 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_69f76dbc22c481908139b694ffde7a0c |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fcf36d2894819089b7db8e91b63c9d |
completed | May 7, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69fcf25c0a108190bfa823474098640b |
completed | May 7, 2026, 8:13 p.m. |
Created at: May 3, 2026, 4:29 p.m.