Triple

T2329446
Position Surface form Disambiguated ID Type / Status
Subject Yekaterina Zhdanova E48366 entity
Predicate familyName P18 FINISHED
Object Zhdanova
Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
 E262028 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: Zhdanova | Statement: [Yekaterina Zhdanova, familyName, Zhdanova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zhdanova
Context triple: [Yekaterina Zhdanova, familyName, Zhdanova]
  • A. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • B. Ruzan
    Ruzan is a surname most notably associated with American television producer and writer Robin Ruzan.
  • C. Lyudmila
    Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
  • D. Svetlana
    Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
  • E. Nadezhda
    Nadezhda is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and meaning "hope."
  • 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: Zhdanova
Triple: [Yekaterina Zhdanova, familyName, Zhdanova]
Generated description
Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zhdanova
Target entity description: Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
  • A. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • B. Ruzan
    Ruzan is a surname most notably associated with American television producer and writer Robin Ruzan.
  • C. Lyudmila
    Lyudmila is a Russian linguist and the former First Lady of Russia, known for being the ex-wife of President Vladimir Putin.
  • D. Svetlana
    Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
  • E. Nadezhda
    Nadezhda is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and meaning "hope."
  • F. None of above. chosen

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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc667235c819086140af9db961203 completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3be86dc8190af185bac9554e7d6 completed March 9, 2026, 11:49 a.m.
NEDg Description generation batch_69aeb46f882881909294a3698ead865e completed March 9, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_69aeb4c715a88190b1009a2cf1d95441 completed March 9, 2026, 11:53 a.m.
Created at: March 4, 2026, 7:50 p.m.