Triple

T16846528
Position Surface form Disambiguated ID Type / Status
Subject Anna Trebunskaya E409553 entity
Predicate familyName P18 FINISHED
Object Trebunskaya
Trebunskaya is the surname of Anna Trebunskaya, a Russian-American professional ballroom dancer known for her appearances on "Dancing with the Stars."
 E1237243 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: Trebunskaya | Statement: [Anna Trebunskaya, familyName, Trebunskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Trebunskaya
Context triple: [Anna Trebunskaya, familyName, Trebunskaya]
  • A. Kutuzovskaya
    Kutuzovskaya is a Moscow Metro station serving the Kutuzovsky Prospekt area in western Moscow.
  • B. Piotrovskaya
    Piotrovskaya is the feminine form of the Russian surname Piotrovsky, typically used for women in Russian naming conventions.
  • C. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • D. Semyonovskaya
    Semyonovskaya is a station on the Moscow Metro, serving the Sokolnicheskaya Line in the eastern part of Moscow.
  • E. Krasnopresnenskaya
    Krasnopresnenskaya is a Moscow Metro station on the city’s circular Koltsevaya Line, known for its deep-level construction and Soviet-era architectural design.
  • 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: Trebunskaya
Triple: [Anna Trebunskaya, familyName, Trebunskaya]
Generated description
Trebunskaya is the surname of Anna Trebunskaya, a Russian-American professional ballroom dancer known for her appearances on "Dancing with the Stars."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Trebunskaya
Target entity description: Trebunskaya is the surname of Anna Trebunskaya, a Russian-American professional ballroom dancer known for her appearances on "Dancing with the Stars."
  • A. Kutuzovskaya
    Kutuzovskaya is a Moscow Metro station serving the Kutuzovsky Prospekt area in western Moscow.
  • B. Piotrovskaya
    Piotrovskaya is the feminine form of the Russian surname Piotrovsky, typically used for women in Russian naming conventions.
  • C. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • D. Semyonovskaya
    Semyonovskaya is a station on the Moscow Metro, serving the Sokolnicheskaya Line in the eastern part of Moscow.
  • E. Krasnopresnenskaya
    Krasnopresnenskaya is a Moscow Metro station on the city’s circular Koltsevaya Line, known for its deep-level construction and Soviet-era architectural design.
  • 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_69d883952b048190887740a980b712ed completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b354eaf081908fe6f84a330d7866 completed April 18, 2026, 4:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb1b47648190909eaaf4e1e8e4c3 completed May 10, 2026, 5:06 p.m.
NEDg Description generation batch_6a00bc22dc1c81909edc5cdb239f0ea8 completed May 10, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_6a00bce879648190acbd5645cd1a4ec8 completed May 10, 2026, 5:14 p.m.
Created at: April 10, 2026, 5:24 a.m.