Triple

T9446243
Position Surface form Disambiguated ID Type / Status
Subject Olga Preobrajenska E227771 entity
Predicate familyName P18 FINISHED
Object Preobrajenska
Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
 E803202 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: Preobrajenska | Statement: [Olga Preobrajenska, familyName, Preobrajenska]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Preobrajenska
Context triple: [Olga Preobrajenska, familyName, Preobrajenska]
  • A. Loznica
    Loznica is a town in western Serbia near the Drina River, known as a regional center with historical and cultural significance.
  • B. Lazarevac
    Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
  • C. Blansko
    Blansko is a small industrial town in the South Moravian Region of the Czech Republic, known as a gateway to the Moravian Karst cave system.
  • D. Obrenovac
    Obrenovac is a suburban municipality of Belgrade in Serbia, known for its industrial facilities and proximity to the Sava River.
  • E. Perovo
    Perovo is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Perovo District of eastern 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: Preobrajenska
Triple: [Olga Preobrajenska, familyName, Preobrajenska]
Generated description
Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Preobrajenska
Target entity description: Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
  • A. Loznica
    Loznica is a town in western Serbia near the Drina River, known as a regional center with historical and cultural significance.
  • B. Lazarevac
    Lazarevac is a suburban municipality of Belgrade in central Serbia, known for its coal mining industry and the Kolubara coal basin.
  • C. Blansko
    Blansko is a small industrial town in the South Moravian Region of the Czech Republic, known as a gateway to the Moravian Karst cave system.
  • D. Obrenovac
    Obrenovac is a suburban municipality of Belgrade in Serbia, known for its industrial facilities and proximity to the Sava River.
  • E. Perovo
    Perovo is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Perovo District of eastern 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_69ca843884488190ad6cbe0153088234 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7f33deb88190bc74968575963ac4 completed April 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d139db9d1081908e2014d6f0e7e925 completed April 4, 2026, 4:18 p.m.
NEDg Description generation batch_69d13a8e79b081908d5b4dce125df678 completed April 4, 2026, 4:21 p.m.
NED2 Entity disambiguation (via description) batch_69d13b1d2cb481908cdcbeb1a6c81794 completed April 4, 2026, 4:23 p.m.
Created at: March 30, 2026, 7:51 p.m.