Triple

T5241151
Position Surface form Disambiguated ID Type / Status
Subject Ekaterina Alexandrovna Shcherbatskaya E118343 entity
Predicate familyName P18 FINISHED
Object Shcherbatskaya
Shcherbatskaya is the surname of Ekaterina Alexandrovna, a fictional Russian noblewoman featured in Leo Tolstoy’s novel "Anna Karenina."
 E515931 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: Shcherbatskaya | Statement: [Ekaterina Alexandrovna Shcherbatskaya, familyName, Shcherbatskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shcherbatskaya
Context triple: [Ekaterina Alexandrovna Shcherbatskaya, familyName, Shcherbatskaya]
  • A. Khodchenkova
    Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
  • B. Ulanova
    Ulanova is a Russian surname most famously associated with Galina Ulanova, one of the greatest ballerinas of the 20th century.
  • C. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • D. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • E. Svetlana
    Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
  • 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: Shcherbatskaya
Triple: [Ekaterina Alexandrovna Shcherbatskaya, familyName, Shcherbatskaya]
Generated description
Shcherbatskaya is the surname of Ekaterina Alexandrovna, a fictional Russian noblewoman featured in Leo Tolstoy’s novel "Anna Karenina."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shcherbatskaya
Target entity description: Shcherbatskaya is the surname of Ekaterina Alexandrovna, a fictional Russian noblewoman featured in Leo Tolstoy’s novel "Anna Karenina."
  • A. Khodchenkova
    Khodchenkova is the surname of Russian actress Svetlana Khodchenkova, known for her work in both Russian cinema and international films.
  • B. Ulanova
    Ulanova is a Russian surname most famously associated with Galina Ulanova, one of the greatest ballerinas of the 20th century.
  • C. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • D. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • E. Svetlana
    Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
  • 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_69bd4467db0881909b3b0982df32cc8f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b2c50508190b84bab216c30cbfe completed March 20, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf29008b38819084e59078210626b2 completed March 21, 2026, 11:25 p.m.
NEDg Description generation batch_69bf2a59d53c81908ce846523f0c94e8 completed March 21, 2026, 11:31 p.m.
NED2 Entity disambiguation (via description) batch_69bf2ad48fc48190bb0c7de4df879c3b completed March 21, 2026, 11:33 p.m.
Created at: March 20, 2026, 1:49 p.m.