Triple

T708857
Position Surface form Disambiguated ID Type / Status
Subject Prague E14162 entity
Predicate officialLanguage P236 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: [Prague, officialLanguage, Czech]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech
Context triple: [Prague, officialLanguage, 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. 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.
  • D. Slovak language
    The Slovak language is a West Slavic language spoken primarily in Slovakia and closely related to Czech and Polish.
  • E. Czech Republic
    The Czech Republic is a landlocked Central European country known for its historic cities like Prague, rich cultural heritage, and membership in major international organizations such as the European Union and NATO.
  • 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_69a493494ec48190ae6751683625a9ba completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a548e6dc819090d31ce33493a396 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dcb1795c8190a178e14509b8b271 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.