Triple

T9582330
Position Surface form Disambiguated ID Type / Status
Subject Прямухино E231202 entity
Predicate nearestTown P350 FINISHED
Object Кувшиново
Кувшиново — небольшой город в Тверской области России, известный как районный центр с развитой лесной и деревообрабатывающей промышленностью.
 E808692 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: Кувшиново | Statement: [Прямухино, nearestTown, Кувшиново]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Кувшиново
Context triple: [Прямухино, nearestTown, Кувшиново]
  • A. Kuznetsovo
    Kuznetsovo is the former name of the town now known as Belogorsk in Russia’s Amur Oblast.
  • B. Pleskov
    Pleskov is an alternative historical or variant name for the Russian city of Pskov, a historic regional center in northwestern Russia.
  • C. Yegoryevsk
    Yegoryevsk is a historic town in Russia, now part of Moscow Oblast, known for its 19th-century architecture and industrial heritage.
  • D. Orekhovo
    Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • E. Konakovo
    Konakovo is a town in Tver Oblast, Russia, situated on the Volga River and known for its power station and riverside recreation.
  • 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: Кувшиново
Triple: [Прямухино, nearestTown, Кувшиново]
Generated description
Кувшиново — небольшой город в Тверской области России, известный как районный центр с развитой лесной и деревообрабатывающей промышленностью.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Кувшиново
Target entity description: Кувшиново — небольшой город в Тверской области России, известный как районный центр с развитой лесной и деревообрабатывающей промышленностью.
  • A. Kuznetsovo
    Kuznetsovo is the former name of the town now known as Belogorsk in Russia’s Amur Oblast.
  • B. Pleskov
    Pleskov is an alternative historical or variant name for the Russian city of Pskov, a historic regional center in northwestern Russia.
  • C. Yegoryevsk
    Yegoryevsk is a historic town in Russia, now part of Moscow Oblast, known for its 19th-century architecture and industrial heritage.
  • D. Orekhovo
    Orekhovo is a Moscow Metro station on the Zamoskvoretskaya Line serving the Orekhovo-Borisovo district in southern Moscow.
  • E. Konakovo
    Konakovo is a town in Tver Oblast, Russia, situated on the Volga River and known for its power station and riverside recreation.
  • 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_69ca848161688190a68d514a0a9d5129 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99cd59008190888eb11f00f61994 completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1616a11688190ba47343e4fd913fd completed April 4, 2026, 7:07 p.m.
NEDg Description generation batch_69d16360b7708190bc23294f267ac695 completed April 4, 2026, 7:15 p.m.
NED2 Entity disambiguation (via description) batch_69d163e654388190ba9b617e6fac18ad completed April 4, 2026, 7:17 p.m.
Created at: March 30, 2026, 8:05 p.m.