Triple
T19504945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian Doll |
E487997
|
entity |
| Predicate | leadCharacter |
P1668
|
FINISHED |
| Object | Nadia Vulvokov |
—
|
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: Nadia Vulvokov | Statement: [Russian Doll, leadCharacter, Nadia Vulvokov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nadia Vulvokov Context triple: [Russian Doll, leadCharacter, Nadia Vulvokov]
-
A.
Nadia Vulvokov
chosen
Nadia Vulvokov is the sharp-tongued, chain-smoking New Yorker who repeatedly dies and relives the same night in the darkly comedic time-loop series "Russian Doll."
-
B.
Tatiana Kukanova
Tatiana Kukanova is best known as the first wife of former Angolan president José Eduardo dos Santos and the mother of his eldest daughter, Isabel dos Santos.
-
C.
Nina Doroshina
Nina Doroshina was a Soviet and Russian actress best known for her leading role in the popular film "Love and Doves."
-
D.
Nina Aleshina
Nina Aleshina was a Soviet architect known for designing Moscow Metro stations, including Kakhovskaya.
-
E.
Anya Derevkova
Anya Derevkova is a Marvel Comics character trained as an elite assassin through the Soviet Black Widow program.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.