Triple

T5670461
Position Surface form Disambiguated ID Type / Status
Subject Zheleznogorsk-Ilimsky E124961 entity
Predicate namedAfter P63 FINISHED
Object Zheleznogorsk (iron city)
Zheleznogorsk (iron city) is a Russian town known for its origins and development around iron ore mining and metallurgical industries.
 E535698 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: Zheleznogorsk (iron city) | Statement: [Zheleznogorsk-Ilimsky, namedAfter, Zheleznogorsk (iron city)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zheleznogorsk (iron city)
Context triple: [Zheleznogorsk-Ilimsky, namedAfter, Zheleznogorsk (iron city)]
  • A. Zheleznogorsk-Ilimsky
    Zheleznogorsk-Ilimsky is a small industrial town in Russia known for its mining and forestry-related industries.
  • B. Kuznetsk
    Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
  • C. Monchegorsk
    Monchegorsk is an industrial town in Russia’s Murmansk Oblast known for its large nickel and copper smelting operations within the Arctic Kola Peninsula region.
  • D. Boksitogorsk
    Boksitogorsk is a small industrial town in northwestern Russia known for its bauxite mining and alumina production.
  • E. Novokuznetskaya
    Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
  • 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: Zheleznogorsk (iron city)
Triple: [Zheleznogorsk-Ilimsky, namedAfter, Zheleznogorsk (iron city)]
Generated description
Zheleznogorsk (iron city) is a Russian town known for its origins and development around iron ore mining and metallurgical industries.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zheleznogorsk (iron city)
Target entity description: Zheleznogorsk (iron city) is a Russian town known for its origins and development around iron ore mining and metallurgical industries.
  • A. Zheleznogorsk-Ilimsky
    Zheleznogorsk-Ilimsky is a small industrial town in Russia known for its mining and forestry-related industries.
  • B. Kuznetsk
    Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
  • C. Monchegorsk
    Monchegorsk is an industrial town in Russia’s Murmansk Oblast known for its large nickel and copper smelting operations within the Arctic Kola Peninsula region.
  • D. Boksitogorsk
    Boksitogorsk is a small industrial town in northwestern Russia known for its bauxite mining and alumina production.
  • E. Novokuznetskaya
    Novokuznetskaya is a Moscow Metro station known for its distinctive Stalinist architecture and richly decorated interiors.
  • 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_69c00828906881908966f270b8f130cf completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02349b570819090f754a2f25e4cf3 completed March 22, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04db2c07c8190a3ee489146951d2d completed March 22, 2026, 8:14 p.m.
NEDg Description generation batch_69c04ee03d1c819096a5acf0358165c1 completed March 22, 2026, 8:19 p.m.
NED2 Entity disambiguation (via description) batch_69c04ffb0fb8819080dff2a9ec6eacb4 completed March 22, 2026, 8:24 p.m.
Created at: March 22, 2026, 3:43 p.m.