Triple
T34918792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VVER-440 |
E1007077
|
entity |
| Predicate | typicalNumberOfFuelAssemblies |
P88230
|
FINISHED |
| Object | 349 |
—
|
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: 349 | Statement: [VVER-440, typicalNumberOfFuelAssemblies, 349]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfFuelAssemblies Context triple: [VVER-440, typicalNumberOfFuelAssemblies, 349]
-
A.
numberOfFuelAssemblies
chosen
Indicates the total count of fuel assemblies associated with or contained in a given system, component, or facility.
-
B.
fuelAssemblyType
Indicates the specific design or classification of a fuel assembly associated with an entity.
-
C.
plannedNumberOfReactors
Indicates the total number of reactors that are intended or scheduled to be built, installed, or operated for a given facility or project.
-
D.
numberOfFuelAssembliesInSpentFuelPoolAtAccident
Indicates the quantity of fuel assemblies that were present in the spent fuel pool at the time of the accident.
-
E.
numberOfReactors
Indicates the quantity of reactors associated with or contained by a given entity.
- 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.