Triple

T17655245
Position Surface form Disambiguated ID Type / Status
Subject Blansko E429605 entity
Predicate locatedIn P40 FINISHED
Object Moravia NE NERFINISHED

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: Moravia | Statement: [Blansko, locatedIn, Moravia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moravia
Context triple: [Blansko, locatedIn, Moravia]
  • A. Moravia chosen
    Moravia is a historical region in the eastern part of the Czech Republic, known for its distinct cultural heritage, wine production, and major cities such as Brno and Olomouc.
  • B. Moravia
    Moravia is a canton in Costa Rica known for its suburban character and proximity to the capital city of San José.
  • C. Bohemia
    Bohemia is a historical region in the western part of the modern Czech Republic, long a cultural and political center of Central Europe.
  • D. Bohemia
    Bohemia is a hamlet in Suffolk County, New York, known for its residential character and proximity to Long Island’s south shore communities.
  • E. North Moravia
    North Moravia is the northern part of the historical Moravia region in the eastern Czech Republic, known for its industrial cities and proximity to the Jeseníky Mountains.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e3fc6e8819080098a3cd0183811 completed April 19, 2026, 5:55 a.m.
Created at: April 10, 2026, 6:06 a.m.