Triple

T2406304
Position Surface form Disambiguated ID Type / Status
Subject Svetlana Khodchenkova E50283 entity
Predicate familyName P18 FINISHED
Object Khodchenkova
Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
 E273527 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: Khodchenkova | Statement: [Svetlana Khodchenkova, familyName, Khodchenkova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Khodchenkova
Context triple: [Svetlana Khodchenkova, familyName, Khodchenkova]
  • A. Zhdanova
    Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
  • B. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • C. Anna Krylova
    Anna Krylova was the wife of Nobel Prize–winning Soviet physicist Peter Kapitza.
  • D. Ruzan
    Ruzan is a surname most notably associated with American television producer and writer Robin Ruzan.
  • E. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • 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: Khodchenkova
Triple: [Svetlana Khodchenkova, familyName, Khodchenkova]
Generated description
Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Khodchenkova
Target entity description: Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
  • A. Zhdanova
    Zhdanova is a Russian-language surname commonly borne by women and associated with several notable figures in Russian and post-Soviet public life.
  • B. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • C. Anna Krylova
    Anna Krylova was the wife of Nobel Prize–winning Soviet physicist Peter Kapitza.
  • D. Ruzan
    Ruzan is a surname most notably associated with American television producer and writer Robin Ruzan.
  • E. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc8fb78408190b99fa8b4dfaaa75d completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69af1f7d18f88190bc19aa6b7b687b8e completed March 9, 2026, 7:29 p.m.
NEDg Description generation batch_69af23f5f7908190a91931a62f61b3f8 completed March 9, 2026, 7:48 p.m.
NED2 Entity disambiguation (via description) batch_69af24468ad08190bfdacfa5a2499d93 completed March 9, 2026, 7:49 p.m.
Created at: March 4, 2026, 7:58 p.m.