Triple
T10108160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Korney Chukovsky |
E218175
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Korney Ivanovich Chukovsky |
E218175
|
NE 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: Korney Ivanovich Chukovsky | Statement: [Korney Chukovsky, fullName, Korney Ivanovich Chukovsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Korney Ivanovich Chukovsky Context triple: [Korney Chukovsky, fullName, Korney Ivanovich Chukovsky]
-
A.
Korney Chukovsky
chosen
Korney Chukovsky was a prominent Soviet and Russian writer, translator, and literary critic best known for his classic children's poetry and fairy tales.
-
B.
Samuil Marshak
Samuil Marshak was a prominent Soviet poet, translator, and children's author whose works became classics of Russian-language literature.
-
C.
Ivan Krylov
Ivan Krylov was a renowned Russian fabulist and poet, best known for his satirical fables that became classics of Russian literature.
-
D.
Mikhail Zoshchenko
Mikhail Zoshchenko was a Soviet satirical writer known for his humorous, colloquial short stories that sharply critiqued everyday life under early Soviet rule.
-
E.
Nikolai Yefremov
Nikolai Yefremov is a Russian actor known for his roles in film and television, including a part in the science fiction thriller "The Darkest Hour."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd0cbd8a48190b2af6177d1249f58 |
completed | April 2, 2026, 2:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3005e007881909f40575d129f2c3d |
completed | April 6, 2026, 12:37 a.m. |
Created at: March 30, 2026, 9:03 p.m.