Triple

T12211378
Position Surface form Disambiguated ID Type / Status
Subject Sarov E290967 entity
Predicate formerName P65 FINISHED
Object Gorky-130
Gorky-130 was the Soviet-era codename for the closed nuclear research city now known as Sarov in Russia.
E969085 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: Gorky-130 | Statement: [Sarov, formerName, Gorky-130]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gorky-130
Context triple: [Sarov, formerName, Gorky-130]
  • A. Gorki-2
    Gorki-2 is a suburban settlement near Moscow, Russia, known as an affluent residential area within Odintsovsky District of Moscow Oblast.
  • B. Gorki-10
    Gorki-10 is a prestigious suburban settlement near Moscow, known for its affluent residences and dachas of Russian political and business elites.
  • C. Shaposhnikov
    Shaposhnikov is a Russian surname most notably associated with Soviet military leader Boris Shaposhnikov.
  • D. Gorky Railway
    Gorky Railway is a major regional railway network in Russia that operates routes across the Volga-Vyatka area, including services through Kazan.
  • E. Dynamo Kursk
    Dynamo Kursk is a prominent Russian women's basketball club that competes in top domestic and European competitions, including the EuroLeague Women.
  • 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: Gorky-130
Triple: [Sarov, formerName, Gorky-130]
Generated description
Gorky-130 was the Soviet-era codename for the closed nuclear research city now known as Sarov in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gorky-130
Target entity description: Gorky-130 was the Soviet-era codename for the closed nuclear research city now known as Sarov in Russia.
  • A. Gorki-2
    Gorki-2 is a suburban settlement near Moscow, Russia, known as an affluent residential area within Odintsovsky District of Moscow Oblast.
  • B. Gorki-10
    Gorki-10 is a prestigious suburban settlement near Moscow, known for its affluent residences and dachas of Russian political and business elites.
  • C. Shaposhnikov
    Shaposhnikov is a Russian surname most notably associated with Soviet military leader Boris Shaposhnikov.
  • D. Gorky Railway
    Gorky Railway is a major regional railway network in Russia that operates routes across the Volga-Vyatka area, including services through Kazan.
  • E. Dynamo Kursk
    Dynamo Kursk is a prominent Russian women's basketball club that competes in top domestic and European competitions, including the EuroLeague Women.
  • 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_69d6ab65923081909acfc61b7a612233 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c915f548190b34a743f0a3bb51a completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a9f45108190a814cdca52e77b5e completed May 2, 2026, 2:30 p.m.
NEDg Description generation batch_69f60bdca250819090b4b4cc84d343f4 completed May 2, 2026, 2:36 p.m.
NED2 Entity disambiguation (via description) batch_69f60cd1668881908f43d895fcfba0aa completed May 2, 2026, 2:40 p.m.
Created at: April 8, 2026, 9:51 p.m.