Triple

T11112920
Position Surface form Disambiguated ID Type / Status
Subject Вішнева E262805 entity
Predicate partOf P40 FINISHED
Object Voranava District E905926 NE FINISHED

How this triple was built (2 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: Voranava District | Statement: [Вішнева, partOf, Voranava District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voranava District
Context triple: [Вішнева, partOf, Voranava District]
  • A. Voranava District chosen
    Voranava District is an administrative district in the Grodno Region of western Belarus, known for its rural settlements and multicultural communities.
  • B. Ilava District
    Ilava District is an administrative district in the Trenčín Region of northwestern Slovakia, known for its mix of industrial towns and rural communities.
  • C. Bytča District
    Bytča District is an administrative district in the Žilina Region of northwestern Slovakia, known for its small towns and historical architecture.
  • D. Michuhol District
    Michuhol District is a central urban district of Incheon, South Korea, known for its residential neighborhoods, commercial areas, and cultural facilities.
  • E. Tapolca District
    Tapolca District is an administrative district in western Hungary, centered on the town of Tapolca and known for its scenic landscapes near Lake Balaton.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa9b46cc8190b19f9f0cc45bf322 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79aa523588190a25d241ccc6a9679 completed April 9, 2026, 12:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69e462f5fe708190835e427b6bf99f13 completed April 19, 2026, 5:07 a.m.
Created at: April 8, 2026, 9:27 p.m.