Triple
T23764700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert-Bourassa generating station |
E587345
|
entity |
| Predicate | hasNumberOfGeneratingUnits |
P112661
|
FINISHED |
| Object | 16 |
—
|
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: 16 | Statement: [Robert-Bourassa generating station, hasNumberOfGeneratingUnits, 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfGeneratingUnits Context triple: [Robert-Bourassa generating station, hasNumberOfGeneratingUnits, 16]
-
A.
generatingUnitCount
chosen
Indicates the number of generating units associated with or involved in a given entity or context.
-
B.
generationUnits
Indicates a relationship where specific units or components are responsible for generating or producing something within a system or process.
-
C.
isMajorSourceOfElectricityFor
Indicates that one entity provides the primary or dominant share of electrical power used by another entity.
-
D.
plannedCapacityMW
Indicates the intended or scheduled power generation capacity of an energy asset, measured in megawatts (MW).
-
E.
grossElectricalCapacity_MWe
Indicates the total electrical power output capacity of a generating unit, measured in megawatts electric (MWe), before accounting for internal power consumption or losses.
- 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_69e2490b8ac48190a6b35f1d5500486b |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bdb4e9248190b64b063637b66702 |
completed | April 29, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:15 p.m.