Triple

T6819699
Position Surface form Disambiguated ID Type / Status
Subject Severodvinsk E156865 entity
Predicate hasFormerName P65 FINISHED
Object Molotovsk
Molotovsk was the former name of the Russian port city now known as Severodvinsk, a major center for shipbuilding and naval industry on the White Sea.
 E622599 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: Molotovsk | Statement: [Severodvinsk, hasFormerName, Molotovsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Molotovsk
Context triple: [Severodvinsk, hasFormerName, Molotovsk]
  • A. Maloyaroslavets
    Maloyaroslavets is a historic town in western Russia known for the 1812 Battle of Maloyaroslavets during Napoleon’s invasion.
  • B. Malinovsky
    Malinovsky is a Russian surname most notably associated with Soviet military commander and Marshal of the Soviet Union Rodion Malinovsky.
  • C. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • D. Dzerzhinsk
    Dzerzhinsk is a major industrial city in western Russia known for its large chemical manufacturing sector and associated environmental issues.
  • E. Tsitska
    Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
  • 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: Molotovsk
Triple: [Severodvinsk, hasFormerName, Molotovsk]
Generated description
Molotovsk was the former name of the Russian port city now known as Severodvinsk, a major center for shipbuilding and naval industry on the White Sea.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Molotovsk
Target entity description: Molotovsk was the former name of the Russian port city now known as Severodvinsk, a major center for shipbuilding and naval industry on the White Sea.
  • A. Maloyaroslavets
    Maloyaroslavets is a historic town in western Russia known for the 1812 Battle of Maloyaroslavets during Napoleon’s invasion.
  • B. Malinovsky
    Malinovsky is a Russian surname most notably associated with Soviet military commander and Marshal of the Soviet Union Rodion Malinovsky.
  • C. Krasnov
    Krasnov is a Russian surname borne by various notable figures in military, political, and cultural history.
  • D. Dzerzhinsk
    Dzerzhinsk is a major industrial city in western Russia known for its large chemical manufacturing sector and associated environmental issues.
  • E. Tsitska
    Tsitska is a Georgian white grape variety from the Imereti region, known for producing fresh, high-acidity wines often used in both still and sparkling styles.
  • 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_69c688298a288190af3f285d57f76bbe completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d35781e88190a45d1386706d4422 completed March 27, 2026, 6:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723e797908190bb0a2d22556b5906 completed March 28, 2026, 12:42 a.m.
NEDg Description generation batch_69c724e915dc8190a82b69939f78420d completed March 28, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69c728ddadd881909c2faa435031a635 completed March 28, 2026, 1:03 a.m.
Created at: March 27, 2026, 2:17 p.m.