Triple

T12510732
Position Surface form Disambiguated ID Type / Status
Subject Sušice E299068 entity
Predicate historicalRegion P915 FINISHED
Object Bohemia E30190 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 | Statement: [Sušice, historicalRegion, Bohemia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bohemia
Context triple: [Sušice, historicalRegion, Bohemia]
  • A. Bohemia chosen
    Bohemia is a historical region in the western part of the modern Czech Republic, long a cultural and political center of Central Europe.
  • B. Bohemia
    Bohemia is a hamlet in Suffolk County, New York, known for its residential character and proximity to Long Island’s south shore communities.
  • C. 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.
  • D. Moravia
    Moravia is a canton in Costa Rica known for its suburban character and proximity to the capital city of San José.
  • E. Czech lands
    The Czech lands are the historical regions of Bohemia, Moravia, and Czech Silesia that form the core territory of today’s Czech Republic.
  • 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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9541d6e508190a4992f328e077467 completed April 10, 2026, 7:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6555e525c8190aa72da362fae1e3e completed May 2, 2026, 7:49 p.m.
Created at: April 8, 2026, 9:57 p.m.