Triple

T40999
Position Surface form Disambiguated ID Type / Status
Subject Volodymyr Zelenskyy E808 entity
Predicate givenName P17 FINISHED
Object Volodymyr
Volodymyr is a common Ukrainian male given name, notably borne by Ukraine’s president Volodymyr Zelenskyy.
 E808 NE FINISHED

How this triple was built (4 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: Volodymyr | Statement: [Volodymyr Zelenskyy, givenName, Volodymyr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Volodymyr
Context triple: [Volodymyr Zelenskyy, givenName, Volodymyr]
  • A. Volodymyr Zelenskyy
    Volodymyr Zelenskyy is the President of Ukraine, a former comedian and actor who became internationally prominent for his leadership during Russia’s full-scale invasion of Ukraine.
  • B. Andrei
    Andrei is a masculine given name commonly used in Slavic and Eastern European countries, equivalent to the English name Andrew.
  • C. Vladimir Putin
    Vladimir Putin is the long-serving Russian leader and former KGB officer who has played a central and often controversial role in post-Soviet Russian politics and global affairs.
  • D. Lutsk
    Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
  • E. Kato Svanidze
    Kato Svanidze was the first wife of Joseph Stalin, remembered primarily for her early death and its profound emotional impact on him.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Volodymyr
Triple: [Volodymyr Zelenskyy, givenName, Volodymyr]
Generated description
Volodymyr is a common Ukrainian male given name, notably borne by Ukraine’s president Volodymyr Zelenskyy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Volodymyr
Target entity description: Volodymyr is a common Ukrainian male given name, notably borne by Ukraine’s president Volodymyr Zelenskyy.
  • A. Volodymyr Zelenskyy chosen
    Volodymyr Zelenskyy is the President of Ukraine, a former comedian and actor who became internationally prominent for his leadership during Russia’s full-scale invasion of Ukraine.
  • B. Andrei
    Andrei is a masculine given name commonly used in Slavic and Eastern European countries, equivalent to the English name Andrew.
  • C. Vladimir Putin
    Vladimir Putin is the long-serving Russian leader and former KGB officer who has played a central and often controversial role in post-Soviet Russian politics and global affairs.
  • D. Lutsk
    Lutsk is a historic city in northwestern Ukraine, known as the administrative center of Volyn Oblast and one of the region’s oldest cultural and economic hubs.
  • E. Kato Svanidze
    Kato Svanidze was the first wife of Joseph Stalin, remembered primarily for her early death and its profound emotional impact on him.
  • F. None of above.

Provenance (5 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_69a247a8f6c08190bac804906d62ed5a completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24ae0b7c4819092220568e8e52ad5 completed Feb. 28, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69a2623cc3648190b2d86352406125e9 completed Feb. 28, 2026, 3:34 a.m.
NEDg Description generation batch_69a262ef9e44819094790f68d3862c5a completed Feb. 28, 2026, 3:37 a.m.
NED2 Entity disambiguation (via description) batch_69a2634b24d08190b4869d235516c2ab completed Feb. 28, 2026, 3:38 a.m.
Created at: Feb. 28, 2026, 1:46 a.m.