Triple

T3727115
Position Surface form Disambiguated ID Type / Status
Subject Czech Air Force E81775 entity
Predicate language P15 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: [Czech Air Force, language, Czech]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech
Context triple: [Czech Air Force, language, 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_69ad8b1b7ef081908d2d381bbf54985a completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcaf7a6908190bd0c3bb5c55ab9ee completed March 8, 2026, 7:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db1102a08190b5965c474dfab6db completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:34 p.m.