Triple
T9242237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pickering Nuclear Generating Station |
E222090
|
entity |
| Predicate | hasReactorUnitCount |
P34726
|
FINISHED |
| Object | multiple reactor units |
—
|
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: multiple reactor units | Statement: [Pickering Nuclear Generating Station, hasReactorUnitCount, multiple reactor units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReactorUnitCount Context triple: [Pickering Nuclear Generating Station, hasReactorUnitCount, multiple reactor units]
-
A.
hasReactorUnit
Indicates that one entity possesses, contains, or is equipped with a specific reactor unit as a component or subsystem.
-
B.
numberOfReactors
chosen
Indicates the quantity of reactors associated with or contained by a given entity.
-
C.
hasCoreUnit
Indicates that an entity includes or is composed around a primary, central, or fundamental unit.
-
D.
hasReactorVendor
Indicates that one entity serves as the supplier or manufacturer of a reactor for another entity.
-
E.
hasMultipleUnitControl
Indicates that a single controller or agent is able to direct, manage, or operate more than one unit simultaneously.
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cd03ec23ec8190993003a826372d40 |
completed | April 1, 2026, 11:39 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:30 p.m.