Triple

T3232385
Position Surface form Disambiguated ID Type / Status
Subject Zinaida Volkova E67769 entity
Predicate familyName P18 FINISHED
Object Volkova
Volkova is a Russian surname commonly borne by individuals of Slavic origin, including notable figures in politics, arts, and sciences.
 E344487 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: Volkova | Statement: [Zinaida Volkova, familyName, Volkova]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Volkova
Context triple: [Zinaida Volkova, familyName, Volkova]
  • A. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • B. Savyolovskaya
    Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
  • C. Savyolovskaya
    Savyolovskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the northern part of the city.
  • D. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • E. Paveletskaya
    Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
  • 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: Volkova
Triple: [Zinaida Volkova, familyName, Volkova]
Generated description
Volkova is a Russian surname commonly borne by individuals of Slavic origin, including notable figures in politics, arts, and sciences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Volkova
Target entity description: Volkova is a Russian surname commonly borne by individuals of Slavic origin, including notable figures in politics, arts, and sciences.
  • A. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • B. Savyolovskaya
    Savyolovskaya is a Moscow Metro station on the Big Circle Line, serving as part of the city’s modern orbital rapid transit network.
  • C. Savyolovskaya
    Savyolovskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the northern part of the city.
  • D. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • E. Paveletskaya
    Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaedb718c8190aae12f763033713a completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e82b6bfc8190a6db566c37ef2eff completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e8b79d308190922a310ff1337eae completed March 12, 2026, 4:24 p.m.
NED2 Entity disambiguation (via description) batch_69b2e9ba41948190b9e4f6f54f32603c completed March 12, 2026, 4:28 p.m.
Created at: March 8, 2026, 3:08 p.m.