Triple

T23043469
Position Surface form Disambiguated ID Type / Status
Subject Semyon Vladimirovich Vysotsky E573804 entity
Predicate givenName P17 FINISHED
Object Semyon 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: Semyon | Statement: [Semyon Vladimirovich Vysotsky, givenName, Semyon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Semyon
Context triple: [Semyon Vladimirovich Vysotsky, givenName, Semyon]
  • A. Semyon chosen
    Semyon is a masculine given name of Russian origin, commonly used in Slavic countries.
  • B. Semyonov
    Semyonov is a common Russian surname borne by numerous notable figures in fields such as literature, science, and military history.
  • C. Anatoly
    Anatoly is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
  • D. Yevgeny
    Yevgeny is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
  • E. Leonid
    Leonid is a masculine given name of Slavic origin, notably borne by Soviet leader Leonid Brezhnev.
  • 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_69e245b9c11481909d06c872214d21af completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18517083c8190a0850da5440e0a73 completed April 29, 2026, 4:12 a.m.
Created at: April 17, 2026, 3:54 p.m.