Triple

T6792507
Position Surface form Disambiguated ID Type / Status
Subject Krasnoyarsk Krai E155967 entity
Predicate contains P35 FINISHED
Object Lesosibirsk
Lesosibirsk is a town in central Siberia, Russia, known historically as a major timber-processing and river port center on the Yenisei River.
 E657307 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: Lesosibirsk | Statement: [Krasnoyarsk Krai, contains, Lesosibirsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lesosibirsk
Context triple: [Krasnoyarsk Krai, contains, Lesosibirsk]
  • A. Bratsk
    Bratsk is a major industrial city in Siberia, Russia, best known for its large hydroelectric power station and aluminum production facilities.
  • B. Volzhsky
    Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
  • C. Tobolsk
    Tobolsk is a historic Siberian town in Russia known for its Kremlin and as a place of exile and imprisonment during the late imperial period.
  • D. Kuznetsk
    Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
  • E. Nizhnevartovsk
    Nizhnevartovsk is a major oil-producing city in western Siberia, Russia, known as one of the centers of the country’s petroleum industry.
  • 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: Lesosibirsk
Triple: [Krasnoyarsk Krai, contains, Lesosibirsk]
Generated description
Lesosibirsk is a town in central Siberia, Russia, known historically as a major timber-processing and river port center on the Yenisei River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lesosibirsk
Target entity description: Lesosibirsk is a town in central Siberia, Russia, known historically as a major timber-processing and river port center on the Yenisei River.
  • A. Bratsk
    Bratsk is a major industrial city in Siberia, Russia, best known for its large hydroelectric power station and aluminum production facilities.
  • B. Volzhsky
    Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
  • C. Tobolsk
    Tobolsk is a historic Siberian town in Russia known for its Kremlin and as a place of exile and imprisonment during the late imperial period.
  • D. Kuznetsk
    Kuznetsk is a city in Penza Oblast, Russia, known as an industrial and transport center in the Volga region.
  • E. Nizhnevartovsk
    Nizhnevartovsk is a major oil-producing city in western Siberia, Russia, known as one of the centers of the country’s petroleum industry.
  • 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_69c6881770fc8190972b2906390380f5 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2ae4d1c819089ac6b3abf11a341 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7eeb79b9c819084738c207aa5c62d completed March 28, 2026, 3:07 p.m.
NEDg Description generation batch_69c7efece4708190b27d973bce45f389 completed March 28, 2026, 3:12 p.m.
NED2 Entity disambiguation (via description) batch_69c7f08355408190a6efdcf66fd3988e completed March 28, 2026, 3:15 p.m.
Created at: March 27, 2026, 2:15 p.m.