Triple

T13181864
Position Surface form Disambiguated ID Type / Status
Subject Gorski Kotar E313748 entity
Predicate hasTown P847 FINISHED
Object Vrbovsko E318764 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: Vrbovsko | Statement: [Gorski Kotar, hasTown, Vrbovsko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vrbovsko
Context triple: [Gorski Kotar, hasTown, Vrbovsko]
  • A. Vrbovsko chosen
    Vrbovsko is a small town in western Croatia known for its mountainous landscape and position along key road and rail routes between Zagreb and the coast.
  • B. Grintovec
    Grintovec is a prominent mountain peak in northern Slovenia, popular with hikers and mountaineers for its challenging routes and panoramic Alpine views.
  • C. Vrčeň
    Vrčeň is a small village and municipality in the Plzeň Region of the Czech Republic.
  • D. Trebnje
    Trebnje is a small town in southeastern Slovenia known as a local cultural and administrative center in the historical region of Lower Carniola.
  • E. Kavečany
    Kavečany is a borough of Košice in eastern Slovakia, known for its hilly landscape, recreational areas, and proximity to major attractions like the Košice Zoo and ski facilities.
  • 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_69d806ae1e08819090d95bfe1538cc17 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c490ed081908ea54edb25c3de90 completed April 10, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f716c1080c81908057f92f320a855b completed May 3, 2026, 9:34 a.m.
Created at: April 9, 2026, 9:15 p.m.