Triple

T17619791
Position Surface form Disambiguated ID Type / Status
Subject Zdeněk Vojtěch Popel of Lobkowicz E429678 entity
Predicate given name P17 FINISHED
Object Zdeněk NE NERFINISHED

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: Zdeněk | Statement: [Zdeněk Vojtěch Popel of Lobkowicz, given name, Zdeněk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zdeněk
Context triple: [Zdeněk Vojtěch Popel of Lobkowicz, given name, Zdeněk]
  • A. Zdeněk chosen
    Zdeněk is a Czech given name commonly used for males, equivalent to the English name Sidney or Dennis in some contexts.
  • B. Jiří
    Jiří is a common Czech male given name, equivalent to George in English.
  • C. Zdeněk Nehoda
    Zdeněk Nehoda is a former Czech footballer, widely regarded as one of Czechoslovakia’s leading forwards of the 1970s and early 1980s.
  • D. Josef Zítek
    Josef Zítek was a 19th-century Czech architect best known for his monumental Neo-Renaissance designs that helped shape Prague’s cultural and urban landscape.
  • E. Augustin Žídek
    Augustin Žídek is a researcher in computational biology and machine learning, known for co-authoring the landmark 2021 Nature paper on AlphaFold’s protein structure prediction.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e37f308190a6aa0a69daff86c7 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46d3547d88190ae3c9ffed63133c9 completed April 19, 2026, 5:50 a.m.
Created at: April 10, 2026, 5:51 a.m.