Triple

T2450717
Position Surface form Disambiguated ID Type / Status
Subject Miroslav Ondříček E53695 entity
Predicate spouse P13 FINISHED
Object Eva Ondříčková
Eva Ondříčková is known as the wife of acclaimed Czech cinematographer Miroslav Ondříček.
E267557 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: Eva Ondříčková | Statement: [Miroslav Ondříček, spouse, Eva Ondříčková]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eva Ondříčková
Context triple: [Miroslav Ondříček, spouse, Eva Ondříčková]
  • A. Dana Vávrová
    Dana Vávrová was a Czech-born German actress and film director known for her acclaimed performances in European cinema and collaborations with director Joseph Vilsmaier.
  • B. Milena Králíčková
    Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
  • C. Hana Benešová
    Hana Benešová was the wife of Czechoslovak statesman and second president Edvard Beneš and served as the country's First Lady during his presidencies.
  • D. Júlia Justína Zavacká
    Júlia Justína Zavacká, later known as Julia Warhola, was the mother of American artist Andy Warhol and an important influence on his life and work.
  • E. Markéta Vaňková
    Markéta Vaňková is a Czech politician who serves as the mayor of Brno, one of the country’s largest cities.
  • 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: Eva Ondříčková
Triple: [Miroslav Ondříček, spouse, Eva Ondříčková]
Generated description
Eva Ondříčková is known as the wife of acclaimed Czech cinematographer Miroslav Ondříček.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Eva Ondříčková
Target entity description: Eva Ondříčková is known as the wife of acclaimed Czech cinematographer Miroslav Ondříček.
  • A. Dana Vávrová
    Dana Vávrová was a Czech-born German actress and film director known for her acclaimed performances in European cinema and collaborations with director Joseph Vilsmaier.
  • B. Milena Králíčková
    Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
  • C. Hana Benešová
    Hana Benešová was the wife of Czechoslovak statesman and second president Edvard Beneš and served as the country's First Lady during his presidencies.
  • D. Júlia Justína Zavacká
    Júlia Justína Zavacká, later known as Julia Warhola, was the mother of American artist Andy Warhol and an important influence on his life and work.
  • E. Markéta Vaňková
    Markéta Vaňková is a Czech politician who serves as the mayor of Brno, one of the country’s largest cities.
  • F. None of above. chosen

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_69ab495d227c8190b26ae6548eeb1019 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd0f402b48190b871b2475983af7e completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0c2a7b08190beb27f6a83208e5c completed March 9, 2026, 4:09 p.m.
NEDg Description generation batch_69aef5de0e4c8190af460b7e2fb2a5eb completed March 9, 2026, 4:31 p.m.
NED2 Entity disambiguation (via description) batch_69aef68a6a18819097876fea0120103b completed March 9, 2026, 4:34 p.m.
Created at: March 6, 2026, 9:43 p.m.