Triple
T18437455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikolay Cherkasov |
E450429
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Lenfilm |
—
|
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: Lenfilm | Statement: [Nikolay Cherkasov, employer, Lenfilm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lenfilm Context triple: [Nikolay Cherkasov, employer, Lenfilm]
-
A.
Lenfilm
chosen
Lenfilm is one of Russia’s oldest and most prominent film studios, based in Saint Petersburg and known for producing many classic Soviet-era movies.
-
B.
Mosfilm
Mosfilm is one of Russia’s largest and oldest film studios, renowned for producing many of the Soviet Union’s most iconic movies.
-
C.
Planfilm
Planfilm is a film distribution company known for handling releases such as Orson Welles' documentary-style film "F for Fake."
-
D.
Teitler Film
Teitler Film is a film production company known for producing feature films such as the family sci-fi adventure "Zathura: A Space Adventure."
-
E.
Zeta Film
Zeta Film is a film production company known for collaborating with other studios such as Central Films on various cinematic projects.
- 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_69d8d381d6388190a9e94e9c658174e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e51c0e04508190bc851a8954ae60e8 |
completed | April 19, 2026, 6:16 p.m. |
Created at: April 10, 2026, 11:29 a.m.