Triple

T8789689
Position Surface form Disambiguated ID Type / Status
Subject Lake Beloslav E209129 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Beloslav E758881 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: Beloslav | Statement: [Lake Beloslav, hasNearbySettlement, Beloslav]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beloslav
Context triple: [Lake Beloslav, hasNearbySettlement, Beloslav]
  • A. Beloslav chosen
    Beloslav is a small industrial town in northeastern Bulgaria known for its glass production and proximity to the city of Varna.
  • B. Blansko
    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.
  • C. Lozova
    Lozova is a town in eastern Ukraine that has historically been a strategic railway and military junction.
  • D. Čáslav
    Čáslav is a historic town in the Czech Republic known for its medieval architecture and location in the fertile Elbe lowlands.
  • E. Kumrovec
    Kumrovec is a small village in northern Croatia best known as the birthplace of Yugoslav leader Josip Broz Tito and as an open-air ethnographic museum preserving traditional Zagorje architecture and culture.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f8b0c108190af53d4bb9b132c5c completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf890b49048190b49c784f84e23496 completed April 3, 2026, 9:31 a.m.
Created at: March 30, 2026, 6:43 p.m.