Triple

T12137046
Position Surface form Disambiguated ID Type / Status
Subject Zora Jandová E289083 entity
Predicate partOf P40 FINISHED
Object Czech culture E31411 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: Czech culture | Statement: [Zora Jandová, partOf, Czech culture]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech culture
Context triple: [Zora Jandová, partOf, Czech culture]
  • A. Czech language
    Czech language is a West Slavic language spoken primarily in the Czech Republic and known for its rich literary tradition and complex grammar.
  • B. Czech American
    A Czech American is a United States citizen or resident of Czech ancestry, reflecting cultural roots in the Czech Republic (formerly part of Czechoslovakia).
  • C. Czechs chosen
    Czechs are a West Slavic ethnic group native primarily to the Czech Republic, known for their distinct language, culture, and historical presence in Central Europe.
  • D. Czech–Slovak languages
    The Czech–Slovak languages are a closely related group of Slavic languages, primarily including Czech and Slovak, spoken in Central Europe.
  • 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_69d6ab4b5e4c81909950b17151eb0951 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9158dd00c819082651891898b91bb completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f690ae408190966bb4fe8feaa7d2 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.