Triple

T4254766
Position Surface form Disambiguated ID Type / Status
Subject Miroslav E95945 entity
Predicate hasLanguageOfUse P207 FINISHED
Object Czech E73024 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 | Statement: [Miroslav, hasLanguageOfUse, Czech]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech
Context triple: [Miroslav, hasLanguageOfUse, Czech]
  • A. Czech language chosen
    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. Middle Czech
    Middle Czech is a historical stage of the Czech language used roughly between the 15th and 17th centuries, marking the transition from Old Czech to Modern Czech.
  • 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. Czechs
    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.
  • 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_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec036e8819087d8585170707545 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a887703c81909a40f23f83154b8c completed March 14, 2026, 6:27 p.m.
Created at: March 12, 2026, 11:06 p.m.