Triple

T7202193
Position Surface form Disambiguated ID Type / Status
Subject Karl Hermann Frank E168773 entity
Predicate regionOfActivity P82 FINISHED
Object Bohemia and Moravia E91859 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: Bohemia and Moravia | Statement: [Karl Hermann Frank, regionOfActivity, Bohemia and Moravia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bohemia and Moravia
Context triple: [Karl Hermann Frank, regionOfActivity, Bohemia and Moravia]
  • A. Bohemia
    Bohemia is a historical region in the western part of the modern Czech Republic, long a cultural and political center of Central Europe.
  • B. Moravia
    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.
  • C. Moravia
    Moravia is a canton in Costa Rica known for its suburban character and proximity to the capital city of San José.
  • D. Czech lands chosen
    The Czech lands are the historical regions of Bohemia, Moravia, and Czech Silesia that form the core territory of today’s Czech Republic.
  • E. Bohemia region
    Bohemia region is a historical region in the western part of the modern Czech Republic, known for its central role in Czech history 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_69c68a5376748190bb500f03df86e93e completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6e94a9ee4819086de79fcdfa1836a completed March 27, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d37f67bc8190bc11ab16f7cbe909 completed March 28, 2026, 1:11 p.m.
Created at: March 27, 2026, 2:52 p.m.