Triple
T33060526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Novovoronezh Nuclear Power Plant |
E845962
|
entity |
| Predicate | numberOfUnitsOperational |
P34085
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Novovoronezh Nuclear Power Plant, numberOfUnitsOperational, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUnitsOperational Context triple: [Novovoronezh Nuclear Power Plant, numberOfUnitsOperational, 2]
-
A.
numberOfUnitsCommanded
Indicates the quantity of units that an entity is in command of within a given context.
-
B.
numberOperational
chosen
Indicates that an entity is currently functioning and available for use in its intended operational capacity.
-
C.
operationalCapability
Indicates the ability or readiness of an entity to perform a specific function, task, or operation effectively under defined conditions.
-
D.
numberOfCountriesWithOperations
Indicates the count of distinct countries in which an entity conducts operations or activities.
-
E.
numberOfMilitaryUnitsRecipients
Indicates the quantity of military units that are received by, or allocated to, the recipient entities in the relationship.
- 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_69f3495333b8819095e9af56855b9061 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a0248062e608190aae1afdae38d2e5a |
completed | May 11, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_6a02465a0d38819084c3a6813fb943fc |
completed | May 11, 2026, 9:12 p.m. |
Created at: May 1, 2026, 1:25 a.m.