Triple
T14753833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pressurised water reactor |
E346679
|
entity |
| Predicate | primaryCoolantRadioactivity |
P38147
|
FINISHED |
| Object | Radioactive |
—
|
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: Radioactive | Statement: [Pressurised water reactor, primaryCoolantRadioactivity, Radioactive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCoolantRadioactivity Context triple: [Pressurised water reactor, primaryCoolantRadioactivity, Radioactive]
-
A.
hasReactorCoolantSystem
Indicates that an entity is equipped with or includes a reactor coolant system used to remove heat from a reactor.
-
B.
thermalNeutronReactor
Indicates that the subject is a nuclear reactor that operates using thermal (low-energy) neutrons to sustain its fission chain reaction.
-
C.
isHighlyRadioactive
chosen
Indicates that the subject emits ionizing radiation at a very high level relative to typical or safe standards.
-
D.
numberOfFuelAssembliesInSpentFuelPoolAtAccident
Indicates the quantity of fuel assemblies that were present in the spent fuel pool at the time of the accident.
-
E.
fuelInReactorCoreAtTimeOfAccident
Indicates that a specified amount or type of fuel was present in the reactor core at the time the accident occurred.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d59df08190a86da5048358bd6e |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8c02e5c08190943c27594026faf7 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:30 a.m.