Triple

T2637953
Position Surface form Disambiguated ID Type / Status
Subject Zora E62792 entity
Predicate isGivenNameOf P17 FINISHED
Object Zora Rozsypalová
Zora Rozsypalová was a Czech actress known for her work in theater and film during the mid-20th century.
 E286945 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: Zora Rozsypalová | Statement: [Zora, isGivenNameOf, Zora Rozsypalová]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zora Rozsypalová
Context triple: [Zora, isGivenNameOf, Zora Rozsypalová]
  • A. Zora Vesecká
    Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
  • B. Milena Králíčková
    Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
  • C. 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.
  • D. Terézia Mora
    Terézia Mora is a Hungarian-born German writer and translator acclaimed for her innovative prose and contributions to contemporary German-language literature.
  • E. 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.
  • 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: Zora Rozsypalová
Triple: [Zora, isGivenNameOf, Zora Rozsypalová]
Generated description
Zora Rozsypalová was a Czech actress known for her work in theater and film during the mid-20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zora Rozsypalová
Target entity description: Zora Rozsypalová was a Czech actress known for her work in theater and film during the mid-20th century.
  • A. Zora Vesecká
    Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
  • B. Milena Králíčková
    Milena Králíčková is a Czech academic and physician who serves as the rector of Charles University in Prague.
  • C. 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.
  • D. Terézia Mora
    Terézia Mora is a Hungarian-born German writer and translator acclaimed for her innovative prose and contributions to contemporary German-language literature.
  • E. 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.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8e470ac8190bd0d6de6805afcd0 completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98bb55f08190bb072c9b106aa748 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af9990f77081908a03b454fad1fad9 completed March 10, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69af99fe48f881908a1a20f5eed8688c completed March 10, 2026, 4:11 a.m.
Created at: March 6, 2026, 9:53 p.m.