Triple
T31281695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pickering A |
E797686
|
entity |
| Predicate | hasReactorTechnology |
P199943
|
FINISHED |
| Object | on-power refuelling capability |
—
|
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: on-power refuelling capability | Statement: [Pickering A, hasReactorTechnology, on-power refuelling capability]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReactorTechnology Context triple: [Pickering A, hasReactorTechnology, on-power refuelling capability]
-
A.
hasNuclearReactorType
Indicates that an entity possesses or is equipped with a specific type or classification of nuclear reactor.
-
B.
hasNuclearReactor
Indicates that an entity possesses, contains, or is equipped with a nuclear reactor.
-
C.
hasReactorUnit
Indicates that one entity possesses, contains, or is equipped with a specific reactor unit as a component or subsystem.
-
D.
hasPowerPlantTechnology
chosen
Indicates that an entity possesses, utilizes, or is associated with a specific power plant technology.
-
E.
reactorTechnologySupplier
Indicates that one entity supplies or provides reactor technology to another 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_69f224def9088190a37034eab3daf57f |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a012594c27081908c80f0e0e6010290 |
completed | May 11, 2026, 12:40 a.m. |
| PD | Predicate disambiguation | batch_6a01252350548190b1df9edc9e581e91 |
completed | May 11, 2026, 12:38 a.m. |
Created at: April 29, 2026, 9:13 p.m.