Triple
T2766641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Maryland (SSBN-738) |
E61353
|
entity |
| Predicate | nuclearReactorType |
P3675
|
FINISHED |
| Object | pressurized water reactor |
—
|
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: pressurized water reactor | Statement: [USS Maryland (SSBN-738), nuclearReactorType, pressurized water reactor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nuclearReactorType Context triple: [USS Maryland (SSBN-738), nuclearReactorType, pressurized water reactor]
-
A.
reactorType
chosen
Indicates the specific kind or category of reactor associated with an entity.
-
B.
nuclearPowered
Indicates that something operates using nuclear energy as its primary power source.
-
C.
nrcReactorUnitNumber
Indicates the specific unit number assigned to a nuclear reactor within an NRC-licensed facility.
-
D.
powerplantType
Indicates the specific kind or category of power plant associated with an entity, based on how it generates energy.
-
E.
numberOfReactors
Indicates the quantity of reactors associated with or contained by a given 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.