Triple

T2167537
Position Surface form Disambiguated ID Type / Status
Subject Serpukhovsko–Timiryazevskaya Line E46944 entity
Predicate hasStation P35 FINISHED
Object Vladykino
Vladykino is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Vladykino district in the northeast of the city.
 E254566 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: Vladykino | Statement: [Serpukhovsko–Timiryazevskaya Line, hasStation, Vladykino]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Vladykino
Context triple: [Serpukhovsko–Timiryazevskaya Line, hasStation, Vladykino]
  • A. Skovorodino
    Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
  • B. Ramenskoye
    Ramenskoye is a town in Moscow Oblast, Russia, located southeast of Moscow and known for its industrial base and proximity to major Moscow airports.
  • C. Orekhovo
    Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • D. Terekhovo
    Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
  • E. Krasnogorsk
    Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside 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: Vladykino
Triple: [Serpukhovsko–Timiryazevskaya Line, hasStation, Vladykino]
Generated description
Vladykino is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Vladykino district in the northeast of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Vladykino
Target entity description: Vladykino is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Vladykino district in the northeast of the city.
  • A. Skovorodino
    Skovorodino is a small town in Russia’s Far Eastern Amur Oblast, known historically as a railway junction on the Trans-Siberian Railway.
  • B. Ramenskoye
    Ramenskoye is a town in Moscow Oblast, Russia, located southeast of Moscow and known for its industrial base and proximity to major Moscow airports.
  • C. Orekhovo
    Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • D. Terekhovo
    Terekhovo is a metro station on Moscow’s Big Circle Line, serving the Terekhovo area in the western part of the city.
  • E. Krasnogorsk
    Krasnogorsk is a city in western Russia that serves as an important administrative and residential center just outside 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_69a88a184cbc8190877791f6552c2484 completed March 4, 2026, 7:38 p.m.
NER Named-entity recognition batch_69abbeac9d688190bfa68715e173771e completed March 7, 2026, 5:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae893ec6248190900ff61f5f3778ce completed March 9, 2026, 8:47 a.m.
NEDg Description generation batch_69ae89bd5c388190ad13a9682a08bba8 completed March 9, 2026, 8:50 a.m.
NED2 Entity disambiguation (via description) batch_69ae8a1ca8848190b265cf0a8c5b909f completed March 9, 2026, 8:51 a.m.
Created at: March 4, 2026, 7:45 p.m.