Triple

T16210727
Position Surface form Disambiguated ID Type / Status
Subject National Heritage Institute E393455 entity
Predicate usesLanguage P238 FINISHED
Object Czech language 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 language | Statement: [National Heritage Institute, usesLanguage, Czech language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech language
Context triple: [National Heritage Institute, usesLanguage, Czech language]
  • 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
    Czech refers to a West Slavic ethnic group native to the Czech Republic, historically associated with the region of Bohemia and the Czech language.
  • C. Czech–Slovak languages
    The Czech–Slovak languages are a closely related group of Slavic languages, primarily including Czech and Slovak, spoken in Central Europe.
  • D. Slovak language
    The Slovak language is a West Slavic language spoken primarily in Slovakia and closely related to Czech and Polish.
  • E. Old Czech
    Old Czech is the earliest documented stage of the Czech language, used in medieval Bohemia and preserved in a variety of religious, legal, and literary texts.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e22713282481909c7c0d0782213461 completed April 17, 2026, 12:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0007932f088190b6c20913cfb932f4 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:03 a.m.