Triple
T17080638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RBMK-1000 |
E414458
|
entity |
| Predicate | regulatoryOutcomeAfterChernobyl |
P9662
|
FINISHED |
| Object | subject to extensive safety upgrades |
—
|
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: subject to extensive safety upgrades | Statement: [RBMK-1000, regulatoryOutcomeAfterChernobyl, subject to extensive safety upgrades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatoryOutcomeAfterChernobyl Context triple: [RBMK-1000, regulatoryOutcomeAfterChernobyl, subject to extensive safety upgrades]
-
A.
reactorStatusBefore2011Accident
Indicates the operational or safety condition of a reactor as it was prior to the 2011 accident event.
-
B.
regulatoryOutcome
chosen
Indicates the result or consequence of a regulatory process, such as approval, rejection, modification, or other formal decision made by a regulatory authority regarding an entity or action.
-
C.
oneOfWorstNuclearAccidentsWith
Indicates that the subject is associated with another entity as being among the worst nuclear accidents together with it.
-
D.
nuclearTestExposure
Indicates that an entity has been subjected to or affected by exposure to nuclear weapons testing or related radioactive fallout.
-
E.
numberOfFuelAssembliesInSpentFuelPoolAtAccident
Indicates the quantity of fuel assemblies that were present in the spent fuel pool at the time of the accident.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe2fe7c819099ab0586b1a119f6 |
completed | April 18, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69e35d642f74819098c014135e249b27 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:34 a.m.