Triple

T19489758
Position Surface form Disambiguated ID Type / Status
Subject Novomoskovsk E487615 entity
Predicate hasFormerName P65 FINISHED
Object Stalinogorsk
Stalinogorsk was the former name of Novomoskovsk, an industrial city in Tula Oblast, Russia, known for its chemical industry.
E1419877 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: Stalinogorsk | Statement: [Novomoskovsk, hasFormerName, Stalinogorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stalinogorsk
Context triple: [Novomoskovsk, hasFormerName, Stalinogorsk]
  • A. Kirovsk
    Kirovsk is a small industrial town in northwestern Russia, situated near Saint Petersburg along the Neva River.
  • B. Kirovsk
    Kirovsk is an industrial town in Russia’s Murmansk Oblast, known for its mining industry and location in the Khibiny Mountains on the Kola Peninsula.
  • C. Kirovskaya
    Kirovskaya was the original name of the Moscow Metro station now known as Chistye Prudy.
  • D. Kirovgrad
    Kirovgrad is a small industrial town in Russia’s Ural region, historically associated with non-ferrous metal mining and processing.
  • E. Tselinograd
    Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
  • 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: Stalinogorsk
Triple: [Novomoskovsk, hasFormerName, Stalinogorsk]
Generated description
Stalinogorsk was the former name of Novomoskovsk, an industrial city in Tula Oblast, Russia, known for its chemical industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Stalinogorsk
Target entity description: Stalinogorsk was the former name of Novomoskovsk, an industrial city in Tula Oblast, Russia, known for its chemical industry.
  • A. Kirovsk
    Kirovsk is an industrial town in Russia’s Murmansk Oblast, known for its mining industry and location in the Khibiny Mountains on the Kola Peninsula.
  • B. Kirovsk
    Kirovsk is a small industrial town in northwestern Russia, situated near Saint Petersburg along the Neva River.
  • C. Kirovskaya
    Kirovskaya was the original name of the Moscow Metro station now known as Chistye Prudy.
  • D. Kirovgrad
    Kirovgrad is a small industrial town in Russia’s Ural region, historically associated with non-ferrous metal mining and processing.
  • E. Tselinograd
    Tselinograd was the Soviet-era name of Kazakhstan’s capital city, now known as Astana.
  • 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_69d8e8d924388190b847cb15bb3d0aff completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6348ad4088190b530f47efca90165 completed April 20, 2026, 2:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08550f1aec819083536adc943e33c2 completed May 16, 2026, 11:29 a.m.
NEDg Description generation batch_6a0855a0d2448190956d254f012e6325 completed May 16, 2026, 11:31 a.m.
NED2 Entity disambiguation (via description) batch_6a0855ff8ff88190933abcb757d8699c completed May 16, 2026, 11:33 a.m.
Created at: April 10, 2026, 1:39 p.m.