Triple

T15563822
Position Surface form Disambiguated ID Type / Status
Subject Vladimir Tenev E371064 entity
Predicate givenName P17 FINISHED
Object Vladimir 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: Vladimir | Statement: [Vladimir Tenev, givenName, Vladimir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vladimir
Context triple: [Vladimir Tenev, givenName, Vladimir]
  • A. Vladimir chosen
    Vladimir is a common Russian male given name of Slavic origin, historically associated with rulers and notably borne by Russian president Vladimir Putin.
  • B. Vladimir
    Vladimir is a historic Russian city east of Moscow, known as one of the medieval capitals of Russia and a key center of the Golden Ring.
  • C. Vladimirko Volodarovich
    Vladimirko Volodarovich was a medieval Rus' prince who ruled the principality of Volhynia in what is now western Ukraine.
  • D. Vladislav
    Vladislav is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • E. Vsevolod
    Vsevolod is a masculine given name of Slavic origin, most notably borne by the influential Russian theatre director Vsevolod Meyerhold.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ddc66448190948280fb0c8d390c completed April 16, 2026, 2:47 a.m.
Created at: April 10, 2026, 4:10 a.m.