Triple

T16816208
Position Surface form Disambiguated ID Type / Status
Subject Matvei Bronstein E408754 entity
Predicate hasRelative P367 FINISHED
Object Korney 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 Chukovsky | Statement: [Matvei Bronstein, hasRelative, Korney Chukovsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Korney Chukovsky
Context triple: [Matvei Bronstein, hasRelative, Korney 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. Lidiya Chukovskaya
    Lidiya Chukovskaya was a Soviet writer, editor, and human rights activist known for her works depicting Stalinist repression and her defense of persecuted authors such as Anna Akhmatova and Aleksandr Solzhenitsyn.
  • D. Ivan Krylov
    Ivan Krylov was a renowned Russian fabulist and poet, best known for his satirical fables that became classics of Russian literature.
  • E. 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.
  • 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_69d88394566c8190b3dcbdc72935f7fa completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b2e1de908190aa3508770fb865cf completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb0f863081908e74dc4a7c91e91d completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:23 a.m.