Triple

T6414549
Position Surface form Disambiguated ID Type / Status
Subject Count E127790 entity
Predicate usedInCountry P715 FINISHED
Object Czech lands E91859 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 lands | Statement: [Count, usedInCountry, Czech lands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Czech lands
Context triple: [Count, usedInCountry, Czech lands]
  • A. Czech lands chosen
    The Czech lands are the historical regions of Bohemia, Moravia, and Czech Silesia that form the core territory of today’s Czech Republic.
  • B. Czech state
    The Czech state is the sovereign national government of the Czech Republic, responsible for administering the country’s public institutions, laws, and cultural heritage.
  • C. Bohemia
    Bohemia is a historical region in the western part of the modern Czech Republic, long a cultural and political center of Central Europe.
  • D. Kingdom of Bohemia
    The Kingdom of Bohemia was a medieval and early modern Central European monarchy centered on Prague that became a key state within the Holy Roman Empire and later the Habsburg Monarchy.
  • E. Moravia
    Moravia is a historical region in the eastern part of the Czech Republic, known for its distinct cultural heritage, wine production, and major cities such as Brno and Olomouc.
  • 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068e6bd3881909b1979de5cdf17fb completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6637d35888190bbe9802229e55df1 completed March 27, 2026, 11:01 a.m.
Created at: March 22, 2026, 4:42 p.m.