Triple

T1037348
Position Surface form Disambiguated ID Type / Status
Subject Kemi E22392 entity
Predicate twinTown P1072 FINISHED
Object 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.
 E182067 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: Kirovsk | Statement: [Kemi, twinTown, Kirovsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kirovsk
Context triple: [Kemi, twinTown, Kirovsk]
  • A. Ulyanov
    Ulyanov is the Russian surname of Vladimir Lenin, the revolutionary leader and founder of the Soviet state.
  • B. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • C. Kostroma
    Kostroma is a historic Russian city northeast of Moscow, known as part of the Golden Ring and for its well-preserved medieval architecture and monasteries.
  • D. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • E. Noginsk
    Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
  • 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: Kirovsk
Triple: [Kemi, twinTown, Kirovsk]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kirovsk
Target entity description: 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.
  • A. Ulyanov
    Ulyanov is the Russian surname of Vladimir Lenin, the revolutionary leader and founder of the Soviet state.
  • B. Astapovo
    Astapovo is a small Russian railway station village historically known as the place where the writer Leo Tolstoy died in 1910.
  • C. Kostroma
    Kostroma is a historic Russian city northeast of Moscow, known as part of the Golden Ring and for its well-preserved medieval architecture and monasteries.
  • D. Voronezh
    Voronezh is a major city in southwestern Russia, situated on the Voronezh River and serving as an important cultural, industrial, and transportation center.
  • E. Noginsk
    Noginsk is a town in western Russia that serves as an industrial and transport center east of Moscow.
  • 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_69a493d848848190aed4011b34b2e8d3 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b82a1014819085bfc077e24c9742 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad519194988190bb0eb59e7fa34dea completed March 8, 2026, 10:38 a.m.
NEDg Description generation batch_69ad52005fc081908655d157d1d99343 completed March 8, 2026, 10:40 a.m.
NED2 Entity disambiguation (via description) batch_69ad526b49f48190a7bf00ad82941dbf completed March 8, 2026, 10:41 a.m.
Created at: March 1, 2026, 7:41 p.m.