Triple

T12779549
Position Surface form Disambiguated ID Type / Status
Subject Legnica E305466 entity
Predicate twinTown P1072 FINISHED
Object Blansko E429605 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: Blansko | Statement: [Legnica, twinTown, Blansko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blansko
Context triple: [Legnica, twinTown, Blansko]
  • A. Blansko chosen
    Blansko is a small industrial town in the South Moravian Region of the Czech Republic, known as a gateway to the Moravian Karst cave system.
  • B. Beloslav
    Beloslav is a small industrial town in northeastern Bulgaria known for its glass production and proximity to the city of Varna.
  • C. Preobrajenska
    Preobrajenska is a Russian surname most notably associated with Olga Preobrajenska, a celebrated ballerina and influential ballet teacher of the late 19th and early 20th centuries.
  • D. Žužemberk
    Žužemberk is a small historic town in southeastern Slovenia, known for its medieval castle and picturesque setting along the Krka River.
  • E. Bednja
    Bednja is a river in northern Croatia that flows through the Zagorje region before joining the Drava River.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e5a5680819095dcd491486d23e7 completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b925b3c81909f5e604c0f457645 completed May 3, 2026, 12:49 a.m.
Created at: April 9, 2026, 5:29 p.m.