Triple

T13016524
Position Surface form Disambiguated ID Type / Status
Subject Ján Svatopluk Presl E322565 entity
Predicate languageOfWorkOrName P15 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: [Ján Svatopluk Presl, languageOfWorkOrName, Czech language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech language
Context triple: [Ján Svatopluk Presl, languageOfWorkOrName, 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. Letiny
    Letiny is a small municipality and village located in the Plzeň Region of the 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ecd04748190ade2530ee5db35fe completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c1147974819090007c21383d5c86 completed May 3, 2026, 3:29 a.m.
Created at: April 9, 2026, 8:51 p.m.