Triple
T22370113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Чайка |
E553016
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Nina Zarechnaya |
—
|
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 Zarechnaya | Statement: [Чайка, mainCharacter, Nina Zarechnaya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nina Zarechnaya Context triple: [Чайка, mainCharacter, Nina Zarechnaya]
-
A.
Nina Zarechnaya
chosen
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.
-
B.
Nina Doroshina
Nina Doroshina was a Soviet and Russian actress best known for her leading role in the popular film "Love and Doves."
-
C.
Nina Kryuchkova
Nina Kryuchkova was the wife of Vladimir Kryuchkov, the longtime KGB chief and key figure in late Soviet politics.
-
D.
Nina Drobysheva
Nina Drobysheva is a Soviet and Russian actress known for her work in mid-20th-century cinema and theater.
-
E.
Nina Grebeshkova
Nina Grebeshkova is a Soviet and Russian film and theater actress best known for her roles in classic comedies of the 1960s and 1970s.
- 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158032b748190ad36c7e3809304e9 |
completed | April 29, 2026, 12:59 a.m. |
Created at: April 16, 2026, 8:44 p.m.