Triple

T1055437
Position Surface form Disambiguated ID Type / Status
Subject Rusyn language E22790 entity
Predicate hasDialect P4251 FINISHED
Object Prešov Rusyn
Prešov Rusyn is a regional variety of the Rusyn language spoken primarily by the Rusyn minority in and around the city of Prešov in eastern Slovakia.
E83895 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: Prešov Rusyn | Statement: [Rusyn language, hasDialect, Prešov Rusyn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prešov Rusyn
Context triple: [Rusyn language, hasDialect, Prešov Rusyn]
  • A. Prešov
    Prešov is a historic city in eastern Slovakia known for its preserved medieval center and role as a regional cultural and economic hub.
  • B. Prešporok
    Prešporok is the historical Slovak name for the city now known as Bratislava, the capital of Slovakia.
  • C. Banská Bystrica
    Banská Bystrica is a historic central Slovak city best known as the main center of the anti-Nazi Slovak National Uprising during World War II.
  • D. Košice
    Košice is a major city in eastern Slovakia known for its historic Old Town, Gothic St. Elisabeth Cathedral, and role as an important cultural and economic center.
  • E. Topoľčany
    Topoľčany is a town in western Slovakia known as the birthplace of several notable Slovak ice hockey players, including Miroslav Šatan.
  • 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: Prešov Rusyn
Triple: [Rusyn language, hasDialect, Prešov Rusyn]
Generated description
Prešov Rusyn is a regional variety of the Rusyn language spoken primarily by the Rusyn minority in and around the city of Prešov in eastern Slovakia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Prešov Rusyn
Target entity description: Prešov Rusyn is a regional variety of the Rusyn language spoken primarily by the Rusyn minority in and around the city of Prešov in eastern Slovakia.
  • A. Prešov chosen
    Prešov is a historic city in eastern Slovakia known for its preserved medieval center and role as a regional cultural and economic hub.
  • B. Prešporok
    Prešporok is the historical Slovak name for the city now known as Bratislava, the capital of Slovakia.
  • C. Banská Bystrica
    Banská Bystrica is a historic central Slovak city best known as the main center of the anti-Nazi Slovak National Uprising during World War II.
  • D. Košice
    Košice is a major city in eastern Slovakia known for its historic Old Town, Gothic St. Elisabeth Cathedral, and role as an important cultural and economic center.
  • E. Topoľčany
    Topoľčany is a town in western Slovakia known as the birthplace of several notable Slovak ice hockey players, including Miroslav Šatan.
  • F. None of above.

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_69a493da02e081908c13ff5e02a0fe7a completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b8d79268819080f3f3f497e91c58 completed March 1, 2026, 10:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bd110ac8190b66163de42bd3034 completed March 7, 2026, 2:53 p.m.
NEDg Description generation batch_69ac3d4b32348190883244f2b8af32a0 completed March 7, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_69ac3dbf5c70819084a942fc97a9b50f completed March 7, 2026, 3:01 p.m.
Created at: March 1, 2026, 7:42 p.m.