Triple

T17525739
Position Surface form Disambiguated ID Type / Status
Subject Liozna E426790 entity
Predicate hasAlternativeName P39 FINISHED
Object Лиозно
Лиозно — это городской посёлок и административный центр Лиозненского района Витебской области Беларуси.
 E1276857 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: Лиозно | Statement: [Liozna, hasAlternativeName, Лиозно]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Лиозно
Context triple: [Liozna, hasAlternativeName, Лиозно]
  • A. Ivangorod
    Ivangorod is a Russian border town on the Narva River, known for its medieval fortress facing the Estonian city of Narva.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Vsevolozhsk
    Vsevolozhsk is a town in northwestern Russia that serves as an important suburban and administrative center near Saint Petersburg.
  • D. Kalyazin
    Kalyazin is a historic town in Tver Oblast, Russia, known for its partially submerged bell tower in the Uglich Reservoir.
  • E. Soligorsk
    Soligorsk is an industrial city in Belarus known for its large potash mining operations and location in the southern part of the Minsk Region.
  • 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: Лиозно
Triple: [Liozna, hasAlternativeName, Лиозно]
Generated description
Лиозно — это городской посёлок и административный центр Лиозненского района Витебской области Беларуси.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Лиозно
Target entity description: Лиозно — это городской посёлок и административный центр Лиозненского района Витебской области Беларуси.
  • A. Ivangorod
    Ivangorod is a Russian border town on the Narva River, known for its medieval fortress facing the Estonian city of Narva.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Vsevolozhsk
    Vsevolozhsk is a town in northwestern Russia that serves as an important suburban and administrative center near Saint Petersburg.
  • D. Kalyazin
    Kalyazin is a historic town in Tver Oblast, Russia, known for its partially submerged bell tower in the Uglich Reservoir.
  • E. Soligorsk
    Soligorsk is an industrial city in Belarus known for its large potash mining operations and location in the southern part of the Minsk Region.
  • 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d6a2548190acf26f2d5d4aab66 completed April 19, 2026, 3:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01dddcb3148190b769e01a159fd5e7 completed May 11, 2026, 1:47 p.m.
NEDg Description generation batch_6a01dfaf934481908753eb760115074a completed May 11, 2026, 1:54 p.m.
NED2 Entity disambiguation (via description) batch_6a01e02a5d9481909cd957c14a4eff3b completed May 11, 2026, 1:56 p.m.
Created at: April 10, 2026, 5:49 a.m.