Triple
T33060545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novovoronezh Nuclear Power Plant |
E845962
|
entity |
| Predicate | thermalCoolingSource |
P54649
|
FINISHED |
| Object | Don River |
—
|
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: Don River | Statement: [Novovoronezh Nuclear Power Plant, thermalCoolingSource, Don River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thermalCoolingSource Context triple: [Novovoronezh Nuclear Power Plant, thermalCoolingSource, Don River]
-
A.
hasCoolingSource
chosen
Indicates that one entity provides or serves as a cooling source for another entity.
-
B.
coolingRequirement
Indicates that an entity requires or is subject to a specific amount or type of cooling to operate within acceptable conditions.
-
C.
coolingMethod
Indicates the technique or process used to remove heat from something or keep it at a lower temperature.
-
D.
heatSource
Indicates that one entity serves as a source of heat or heating for another entity.
-
E.
coolingStyle
Indicates the method or mechanism by which something is cooled or has its temperature reduced.
- 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_69f3495333b8819095e9af56855b9061 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d27120988190aacec621cf2bf0e8 |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:25 a.m.