Triple

T11802311
Position Surface form Disambiguated ID Type / Status
Subject Mikhail Piotrovsky E280655 entity
Predicate familyName P18 FINISHED
Object Piotrovsky E280655 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: Piotrovsky | Statement: [Mikhail Piotrovsky, familyName, Piotrovsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Piotrovsky
Context triple: [Mikhail Piotrovsky, familyName, Piotrovsky]
  • A. Piotrovsky chosen
    Piotrovsky is a Russian surname most prominently associated with Mikhail Piotrovsky, the long-serving director of the State Hermitage Museum in Saint Petersburg.
  • B. Chernyakhovsky
    Chernyakhovsky is a Slavic surname most notably associated with Soviet General Ivan Chernyakhovsky, a prominent commander during World War II.
  • C. Gorkovskaya
    Gorkovskaya was the former name of Moscow’s central Tverskaya metro station, reflecting its Soviet-era designation.
  • D. Danilov
    Danilov is a Russian masculine surname, from which the feminine form Danilova is derived.
  • E. Krasnopresnenskaya
    Krasnopresnenskaya is a Moscow Metro station on the city’s circular Koltsevaya Line, known for its deep-level construction and Soviet-era architectural design.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a5a2048190b68027f622366079 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f41775f4348190a82e8f6c265c9c36 completed May 1, 2026, 3:01 a.m.
Created at: April 8, 2026, 9:42 p.m.