Triple

T13155253
Position Surface form Disambiguated ID Type / Status
Subject Kaluzhsko–Rizhskaya Line E312566 entity
Predicate hasStation P35 FINISHED
Object Belyayevo
Belyayevo is a Moscow Metro station on the Kaluzhsko–Rizhskaya Line serving the Belyayevo district in southwestern Moscow.
 E1055960 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: Belyayevo | Statement: [Kaluzhsko–Rizhskaya Line, hasStation, Belyayevo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Belyayevo
Context triple: [Kaluzhsko–Rizhskaya Line, hasStation, Belyayevo]
  • A. Zayukovo
    Zayukovo is a rural locality in the Kabardino-Balkar Republic of Russia situated along the Baksan River in the North Caucasus region.
  • 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. Petrovskoye
    Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
  • D. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • E. Zyablikovo
    Zyablikovo is a station on the Moscow Metro, serving as a southern terminus and an important interchange point in the city’s transit 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: Belyayevo
Triple: [Kaluzhsko–Rizhskaya Line, hasStation, Belyayevo]
Generated description
Belyayevo is a Moscow Metro station on the Kaluzhsko–Rizhskaya Line serving the Belyayevo district in southwestern Moscow.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Belyayevo
Target entity description: Belyayevo is a Moscow Metro station on the Kaluzhsko–Rizhskaya Line serving the Belyayevo district in southwestern Moscow.
  • A. Zayukovo
    Zayukovo is a rural locality in the Kabardino-Balkar Republic of Russia situated along the Baksan River in the North Caucasus region.
  • 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. Petrovskoye
    Petrovskoye was the original Russian fortress settlement that later developed into the modern city of Makhachkala in Dagestan, Russia.
  • D. Yuzovka
    Yuzovka was the original name of the industrial settlement in eastern Ukraine that later developed into the city of Donetsk.
  • E. Zyablikovo
    Zyablikovo is a station on the Moscow Metro, serving as a southern terminus and an important interchange point in the city’s transit 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c06ccb881909390df18e1a6f7ed completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7941e0560819080eee43a9ed0e1bb completed May 3, 2026, 6:29 p.m.
NEDg Description generation batch_69f798aab9c48190acaa78864e89411f completed May 3, 2026, 6:49 p.m.
NED2 Entity disambiguation (via description) batch_69f79943e4f4819098fa82cb6a32e08a completed May 3, 2026, 6:51 p.m.
Created at: April 9, 2026, 9:12 p.m.