Triple
T17080637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RBMK-1000 |
E414458
|
entity |
| Predicate | numberOfFuelChannelsApproximate |
P125799
|
FINISHED |
| Object | about 1661 channels |
—
|
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: about 1661 channels | Statement: [RBMK-1000, numberOfFuelChannelsApproximate, about 1661 channels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFuelChannelsApproximate Context triple: [RBMK-1000, numberOfFuelChannelsApproximate, about 1661 channels]
-
A.
numberOfSpectralChannels
Indicates the relationship specifying how many distinct spectral channels are associated with an entity or measurement.
-
B.
numberOfGasCells
Indicates the quantity of distinct gas cells associated with or contained within a given entity or system.
-
C.
numberOfFullRangeChannels
Indicates the total count of channels that operate over the complete available range of values or frequencies.
-
D.
numberOfAdditionalChannels
Indicates the quantity of extra channels added beyond a base or default set in a given context.
-
E.
numberOfFuelAssemblies
Indicates the total count of fuel assemblies associated with or contained in a given system, component, or facility.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69e3753f93c88190808fec5692f66699 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:34 a.m.