Triple
T3881072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calvert Cliffs Nuclear Power Plant |
E92822
|
entity |
| Predicate | netElectricalCapacity |
P35295
|
FINISHED |
| Object | over 1600 MWe |
—
|
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: over 1600 MWe | Statement: [Calvert Cliffs Nuclear Power Plant, netElectricalCapacity, over 1600 MWe]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: netElectricalCapacity Context triple: [Calvert Cliffs Nuclear Power Plant, netElectricalCapacity, over 1600 MWe]
-
A.
netElectricalCapacity_MWe
chosen
Indicates the relationship specifying an entity’s net electrical power generation capacity, measured in megawatts electric (MWe), after accounting for internal power consumption.
-
B.
electricityUse
Indicates the amount or pattern of electrical energy consumed by an entity during a specified period or activity.
-
C.
typeOfElectricity
Indicates that one entity specifies the particular kind or category of electricity associated with another entity.
-
D.
batteryCapacity
Indicates the amount of electrical energy a battery can store or deliver, typically expressed in units like mAh or Wh.
-
E.
numberOfPowerhouses
Indicates the quantity of powerhouse entities associated with or contained by a given subject.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.