Triple
T19604404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashiwazaki-Kariwa Nuclear Power Plant |
E470565
|
entity |
| Predicate | hasEmergencyDieselGenerators |
P70489
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Kashiwazaki-Kariwa Nuclear Power Plant, hasEmergencyDieselGenerators, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyDieselGenerators Context triple: [Kashiwazaki-Kariwa Nuclear Power Plant, hasEmergencyDieselGenerators, true]
-
A.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
-
B.
hasNearbyPowerPlants
Indicates that one entity is located close to one or more power plants.
-
C.
hasTurbines
Indicates that one entity is equipped with, contains, or includes one or more turbines in relation to another entity.
-
D.
hasBackupDieselCapacityApprox
chosen
Indicates that an entity possesses an approximate amount of backup diesel-powered capacity available for use.
-
E.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64081af6c8190868b73b07c874cd5 |
completed | April 20, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69e514e166dc8190a0f147e0b4c8bbe7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.