Triple
T29471939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Служебный роман |
E747531
|
entity |
| Predicate | оператор-постановщик |
P179
|
FINISHED |
| Object | Владимир Нахабцев |
—
|
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: Владимир Нахабцев | Statement: [Служебный роман, оператор-постановщик, Владимир Нахабцев]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: оператор-постановщик Context triple: [Служебный роман, оператор-постановщик, Владимир Нахабцев]
-
A.
initialOperator
Indicates that an entity serves as the first or primary operator initiating a process, action, or operation involving another entity.
-
B.
designedOperator
Indicates that an entity (typically a person or organization) intentionally created or planned the specified operator (such as a function, mechanism, or process) for a particular purpose.
-
C.
typicalOperator
Indicates that an entity commonly or normally performs operations on, or acts upon, another entity in a standard or expected manner.
-
D.
operator
chosen
Indicates that one entity functions as the operator (controller or handler) of another entity, such as a system, device, or process.
-
E.
dominantOperatorInRussia
Indicates that an operator holds a leading or controlling market position within Russia.
- 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_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:57 p.m.