Triple
T17469443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eldar Ryazanov |
E425365
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Nina Skuybina |
—
|
NE NERFINISHED |
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: Nina Skuybina | Statement: [Eldar Ryazanov, spouse, Nina Skuybina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nina Skuybina Context triple: [Eldar Ryazanov, spouse, Nina Skuybina]
-
A.
Nina Grebeshkova
chosen
Nina Grebeshkova is a Soviet and Russian film and theater actress best known for her roles in classic comedies of the 1960s and 1970s.
-
B.
Nina Zarechnaya
Nina Zarechnaya is a young, idealistic aspiring actress in Anton Chekhov’s play "The Seagull," whose romantic disillusionment and artistic struggles form one of the drama’s central emotional arcs.
-
C.
Nina Drobysheva
Nina Drobysheva is a Soviet and Russian actress known for her work in mid-20th-century cinema and theater.
-
D.
Nina Kryuchkova
Nina Kryuchkova was the wife of Vladimir Kryuchkov, the longtime KGB chief and key figure in late Soviet politics.
-
E.
Nina Ruslanova
Nina Ruslanova was a Soviet and Russian film and theater actress known for her powerful character roles and collaborations with prominent directors.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451aad4a08190be7e25841da8e952 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.