Triple

T7276584
Position Surface form Disambiguated ID Type / Status
Subject Dominika Egorova E163044 entity
Predicate familyName P18 FINISHED
Object Egorova
Egorova is a Russian surname most notably associated with the fictional character Dominika Egorova, a former ballerina turned intelligence operative in the "Red Sparrow" spy thriller series.
 E653802 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: Egorova | Statement: [Dominika Egorova, familyName, Egorova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Egorova
Context triple: [Dominika Egorova, familyName, Egorova]
  • A. Vasilyeva
    Vasilyeva is a common Russian surname, typically the feminine form of Vasilyev, derived from the given name Vasily.
  • B. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • C. Volkova
    Volkova is a Russian surname commonly borne by individuals of Slavic origin, including notable figures in politics, arts, and sciences.
  • D. Ulyanova
    Ulyanova is a Russian surname most notably borne by the family of Vladimir Lenin, including his sister Maria Ulyanova.
  • 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: Egorova
Triple: [Dominika Egorova, familyName, Egorova]
Generated description
Egorova is a Russian surname most notably associated with the fictional character Dominika Egorova, a former ballerina turned intelligence operative in the "Red Sparrow" spy thriller series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Egorova
Target entity description: Egorova is a Russian surname most notably associated with the fictional character Dominika Egorova, a former ballerina turned intelligence operative in the "Red Sparrow" spy thriller series.
  • A. Vasilyeva
    Vasilyeva is a common Russian surname, typically the feminine form of Vasilyev, derived from the given name Vasily.
  • B. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • C. Volkova
    Volkova is a Russian surname commonly borne by individuals of Slavic origin, including notable figures in politics, arts, and sciences.
  • D. Ulyanova
    Ulyanova is a Russian surname most notably borne by the family of Vladimir Lenin, including his sister Maria Ulyanova.
  • 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_69c6885c5964819085b209701769877f completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb2f239c819097c1ac4d6de8b0e5 completed March 27, 2026, 8:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db3110688190bf52180ea159c91c completed March 28, 2026, 1:44 p.m.
NEDg Description generation batch_69c7dbf65fb08190ae8a9c4e57d42e97 completed March 28, 2026, 1:47 p.m.
NED2 Entity disambiguation (via description) batch_69c7dc6873a081908ea4e953430ec20b completed March 28, 2026, 1:49 p.m.
Created at: March 27, 2026, 2:59 p.m.