Triple

T8689770
Position Surface form Disambiguated ID Type / Status
Subject Zbigniew E206255 entity
Predicate isCognateWith P2527 FINISHED
Object Zbyněk
Zbyněk is a Czech given name, cognate with the Polish name Zbigniew, traditionally borne by several notable historical and cultural figures in the Czech lands.
 E506084 NE FINISHED

How this triple was built (4 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: Zbyněk | Statement: [Zbigniew, isCognateWith, Zbyněk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zbyněk
Context triple: [Zbigniew, isCognateWith, Zbyněk]
  • A. Zdeněk
    Zdeněk is a Czech given name commonly used for males, equivalent to the English name Sidney or Dennis in some contexts.
  • B. Vojtech
    Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • C. Oldřich
    Oldřich is a Czech masculine given name traditionally borne by several notable historical and cultural figures in the Czech lands.
  • 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. Zbyněk Žába
    Zbyněk Žába was a Czech Egyptologist known for his significant contributions to the study of ancient Egypt and for helping establish modern Egyptology in Czechoslovakia.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zbyněk
Triple: [Zbigniew, isCognateWith, Zbyněk]
Generated description
Zbyněk is a Czech given name, cognate with the Polish name Zbigniew, traditionally borne by several notable historical and cultural figures in the Czech lands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zbyněk
Target entity description: Zbyněk is a Czech given name, cognate with the Polish name Zbigniew, traditionally borne by several notable historical and cultural figures in the Czech lands.
  • A. Zdeněk
    Zdeněk is a Czech given name commonly used for males, equivalent to the English name Sidney or Dennis in some contexts.
  • B. Vojtech
    Vojtech is a masculine given name of Slavic origin, commonly used in Central and Eastern Europe.
  • C. Oldřich
    Oldřich is a Czech masculine given name traditionally borne by several notable historical and cultural figures in the Czech lands.
  • 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. Zbyněk Žába chosen
    Zbyněk Žába was a Czech Egyptologist known for his significant contributions to the study of ancient Egypt and for helping establish modern Egyptology in Czechoslovakia.
  • F. None of above.

Provenance (5 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5734602c81909a0687e00f4a4a26 completed March 31, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6edeef308190b6acfe324552b1cf completed April 3, 2026, 7:40 a.m.
NEDg Description generation batch_69cf70c981808190856827fbcd4c4671 completed April 3, 2026, 7:48 a.m.
NED2 Entity disambiguation (via description) batch_69cf71914ec48190bd623d8d773e7ca7 completed April 3, 2026, 7:51 a.m.
Created at: March 30, 2026, 6:33 p.m.