Triple

T2331574
Position Surface form Disambiguated ID Type / Status
Subject Arbatsko–Pokrovskaya Line E44213 entity
Predicate hasTerminus P388 FINISHED
Object Shchyolkovskaya
Shchyolkovskaya is a Moscow Metro station serving as the eastern terminus of the Arbatsko–Pokrovskaya Line.
 E256870 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: Shchyolkovskaya | Statement: [Arbatsko–Pokrovskaya Line, hasTerminus, Shchyolkovskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shchyolkovskaya
Context triple: [Arbatsko–Pokrovskaya Line, hasTerminus, Shchyolkovskaya]
  • A. Alliluyeva
    Alliluyeva is a Russian surname most notably borne by Nadezhda Alliluyeva, the second wife of Soviet leader Joseph Stalin.
  • B. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • C. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • D. Khokhlova
    Khokhlova is a Russian surname most famously borne by Olga Khokhlova, a Ukrainian-Russian ballerina and the first wife of Pablo Picasso.
  • E. Gagarina
    Gagarina is a Russian surname most notably associated with Yelena Gagarina, the daughter of cosmonaut Yuri Gagarin and a prominent museum director.
  • 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: Shchyolkovskaya
Triple: [Arbatsko–Pokrovskaya Line, hasTerminus, Shchyolkovskaya]
Generated description
Shchyolkovskaya is a Moscow Metro station serving as the eastern terminus of the Arbatsko–Pokrovskaya Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shchyolkovskaya
Target entity description: Shchyolkovskaya is a Moscow Metro station serving as the eastern terminus of the Arbatsko–Pokrovskaya Line.
  • A. Alliluyeva
    Alliluyeva is a Russian surname most notably borne by Nadezhda Alliluyeva, the second wife of Soviet leader Joseph Stalin.
  • B. Kuntsevskaya
    Kuntsevskaya is a Moscow Metro station on the Big Circle Line serving the Kuntsevo District in western Moscow.
  • C. Govardeyskaya
    Govardeyskaya is a Moscow Metro station on the Kalininsko–Solntsevskaya line.
  • D. Khokhlova
    Khokhlova is a Russian surname most famously borne by Olga Khokhlova, a Ukrainian-Russian ballerina and the first wife of Pablo Picasso.
  • E. Gagarina
    Gagarina is a Russian surname most notably associated with Yelena Gagarina, the daughter of cosmonaut Yuri Gagarin and a prominent museum director.
  • 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_69a889132b488190bbb43ad4780ddd92 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc669956881908b8d9784d6a06acf completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae89773c88819087a294d7c0f90f73 completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8ae2ab7481909d265e56369f68e2 completed March 9, 2026, 8:54 a.m.
NED2 Entity disambiguation (via description) batch_69ae8b6c553481908b2b7b1f880b814d completed March 9, 2026, 8:57 a.m.
Created at: March 4, 2026, 7:51 p.m.