Triple

T16487162
Position Surface form Disambiguated ID Type / Status
Subject Ilya Kabakov E400475 entity
Predicate familyName P18 FINISHED
Object Kabakov E400475 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: Kabakov | Statement: [Ilya Kabakov, familyName, Kabakov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabakov
Context triple: [Ilya Kabakov, familyName, Kabakov]
  • A. Kazansky
    Kazansky refers to Tom "Iceman" Kazansky, the elite U.S. Navy fighter pilot character from the "Top Gun" film series.
  • B. Totleben
    Totleben is a German-origin surname most notably associated with Eduard Totleben, a prominent 19th-century Russian military engineer and general.
  • C. Tartakovsky
    Tartakovsky is a surname most prominently associated with Genndy Tartakovsky, the acclaimed animator and creator of series like Dexter’s Laboratory, Samurai Jack, and Primal.
  • D. Batitsky
    Batitsky is a Russian surname most notably associated with Soviet military commander Pavel Batitsky.
  • E. Ilya Kabakov chosen
    Ilya Kabakov was a pioneering Russian-American conceptual artist best known for his large-scale, narrative-driven installations that explore Soviet life, memory, and utopian ideals.
  • 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e078d0c8190a5698a5eb9df22d4 completed April 18, 2026, 7:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00582275308190a0fb3944d74916cf completed May 10, 2026, 10:04 a.m.
Created at: April 10, 2026, 5:13 a.m.