Triple

T23019438
Position Surface form Disambiguated ID Type / Status
Subject Slovakia E573120 entity
Predicate hasRegion P285 FINISHED
Object Prešov Region E130151 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: Prešov Region | Statement: [Slovakia, hasRegion, Prešov Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prešov Region
Context triple: [Slovakia, hasRegion, Prešov Region]
  • A. Prešov Region chosen
    The Prešov Region is an administrative region in northeastern Slovakia known for its mountainous landscapes, historic towns, and proximity to the High Tatras.
  • B. Trnava Region
    Trnava Region is an administrative region in western Slovakia known for its historic towns, agricultural landscape, and proximity to the capital, Bratislava.
  • C. Košice Region
    Košice Region is an administrative region in eastern Slovakia that includes the city of Košice as its largest urban center.
  • D. Banská Bystrica region
    The Banská Bystrica region is a central Slovak area historically known as a key stronghold and focal point of anti-Nazi resistance during World War II.
  • E. Trenčín Region
    Trenčín Region is an administrative region in western Slovakia known for its historic towns, including the city of Trenčín, and its cultural and economic significance.
  • 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_69e245b821008190b0e09cb02092aae1 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f183e777cc81908c0b0bfd9d5a717c completed April 29, 2026, 4:07 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c5daa149c8190aa95908bd6dd8767 completed May 19, 2026, 12:55 p.m.
Created at: April 17, 2026, 3:52 p.m.