Triple

T17525738
Position Surface form Disambiguated ID Type / Status
Subject Liozna E426790 entity
Predicate hasAlternativeName P39 FINISHED
Object Ліозна
Ліозна — це селище міського типу в Білорусі, розташоване у Вітебській області поблизу кордону з Росією.
E1274087 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: Ліозна | Statement: [Liozna, hasAlternativeName, Ліозна]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ліозна
Context triple: [Liozna, hasAlternativeName, Ліозна]
  • A. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • B. Liévin
    Liévin is a commune in the Pas-de-Calais department in northern France, historically linked to coal mining and now part of the Lens–Liévin urban area.
  • C. Loncin
    Loncin is a locality in the municipality of Ans in the province of Liège, Belgium.
  • D. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • E. Pamiers
    Pamiers is a historic commune in southwestern France, known as the largest town in the Ariège department and noted for its medieval architecture and role as a local economic center.
  • 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: Ліозна
Triple: [Liozna, hasAlternativeName, Ліозна]
Generated description
Ліозна — це селище міського типу в Білорусі, розташоване у Вітебській області поблизу кордону з Росією.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ліозна
Target entity description: Ліозна — це селище міського типу в Білорусі, розташоване у Вітебській області поблизу кордону з Росією.
  • A. Brest
    Brest is a major port city in northwestern France that serves as one of the country’s principal naval and maritime centers.
  • B. Liévin
    Liévin is a commune in the Pas-de-Calais department in northern France, historically linked to coal mining and now part of the Lens–Liévin urban area.
  • C. Loncin
    Loncin is a locality in the municipality of Ans in the province of Liège, Belgium.
  • D. Lübars
    Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
  • E. Pamiers
    Pamiers is a historic commune in southwestern France, known as the largest town in the Ariège department and noted for its medieval architecture and role as a local economic center.
  • 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_6a01c9473100819081079a0db51391cc completed May 11, 2026, 12:19 p.m.
NEDg Description generation batch_6a01cb2016f8819090e8ec20428cfdaf completed May 11, 2026, 12:27 p.m.
NED2 Entity disambiguation (via description) batch_6a01cbad7bf481909c754049686c5b39 completed May 11, 2026, 12:29 p.m.
Created at: April 10, 2026, 5:49 a.m.