Triple
T29472210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Джентльмены удачи |
E747539
|
entity |
| Predicate | оператор |
P179
|
FINISHED |
| Object | Сергей Вронский |
—
|
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: Сергей Вронский | Statement: [Джентльмены удачи, оператор, Сергей Вронский]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: оператор Context triple: [Джентльмены удачи, оператор, Сергей Вронский]
-
A.
operator
chosen
Indicates that one entity functions as the operator (controller or handler) of another entity, such as a system, device, or process.
-
B.
operatorSymbol
Indicates the symbolic notation used to represent an operator in an expression or formal system.
-
C.
operatorBase
Indicates that one entity serves as the primary or foundational operator for another entity or operation.
-
D.
otherOperator
Indicates a relationship where one operator is distinguished from, or serves as an alternative to, another operator within the same context or system.
-
E.
operatorPeriod
Indicates the time span during which an operator is active, responsible, or in effect for a given operation or system.
- 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_69f0bd42cf308190bb01b20bc5b7c2d0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f66babf5e08190b8e1007546f3881a |
completed | May 2, 2026, 9:25 p.m. |
| PD | Predicate disambiguation | batch_69f6659b62fc8190b21555d0ba54db2d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 3:58 p.m.