Triple

T1946827
Position Surface form Disambiguated ID Type / Status
Subject Big Circle Line E42071 entity
Predicate hasStation P35 FINISHED
Object Zyuzino
Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
E227082 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: Zyuzino | Statement: [Big Circle Line, hasStation, Zyuzino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zyuzino
Context triple: [Big Circle Line, hasStation, Zyuzino]
  • A. Chernyakhovsky
    Chernyakhovsky is a Slavic surname most notably associated with Soviet General Ivan Chernyakhovsky, a prominent commander during World War II.
  • B. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • C. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • D. Nikitin
    Nikitin is a Russian surname borne by numerous notable figures in fields such as art, science, and sports.
  • E. Rubtsovsk
    Rubtsovsk is an industrial city in Altai Krai, Russia, known as the birthplace of Raisa Gorbacheva and for its role as a regional agricultural and machinery center.
  • 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: Zyuzino
Triple: [Big Circle Line, hasStation, Zyuzino]
Generated description
Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Zyuzino
Target entity description: Zyuzino is a Moscow Metro station on the Big Circle Line serving the Zyuzino District in southern Moscow.
  • A. Chernyakhovsky
    Chernyakhovsky is a Slavic surname most notably associated with Soviet General Ivan Chernyakhovsky, a prominent commander during World War II.
  • B. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • C. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • D. Nikitin
    Nikitin is a Russian surname borne by numerous notable figures in fields such as art, science, and sports.
  • E. Rubtsovsk
    Rubtsovsk is an industrial city in Altai Krai, Russia, known as the birthplace of Raisa Gorbacheva and for its role as a regional agricultural and machinery center.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb32ebae881908f7541301f0198ae completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0acad6408190ac31a3f817df1360 completed March 8, 2026, 11:48 p.m.
NEDg Description generation batch_69ae0b9c8d3881908582542da9176ede completed March 8, 2026, 11:51 p.m.
NED2 Entity disambiguation (via description) batch_69ae0f609210819093427e1d73b61198 completed March 9, 2026, 12:08 a.m.
Created at: March 4, 2026, 7:36 p.m.