Triple

T5517217
Position Surface form Disambiguated ID Type / Status
Subject Milan Kundera E144713 entity
Predicate spouse P13 FINISHED
Object Věra Hrabánková
Věra Hrabánková is the wife of Czech-born writer Milan Kundera and has long been known as his close partner and literary collaborator.
 E534580 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: Věra Hrabánková | Statement: [Milan Kundera, spouse, Věra Hrabánková]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Věra Hrabánková
Context triple: [Milan Kundera, spouse, Věra Hrabánková]
  • A. Věra Davidová
    Věra Davidová was the daughter of Ottla Kafka, making her a niece of the writer Franz Kafka.
  • B. Milada Rádlová
    Milada Rádlová was the daughter of Emil Hácha, the third president of Czechoslovakia during the early years of World War II.
  • C. Marie Jana Körbelová
    Marie Jana Körbelová is the birth name of Madeleine Albright, the first female United States Secretary of State and a prominent American diplomat.
  • D. Dagmar Pecková
    Dagmar Pecková is a renowned Czech mezzo-soprano opera singer known for her performances on major European stages and her interpretations of both classical and contemporary repertoire.
  • E. Zora Rozsypalová
    Zora Rozsypalová was a Czech actress known for her work in theater and film during the mid-20th century.
  • 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: Věra Hrabánková
Triple: [Milan Kundera, spouse, Věra Hrabánková]
Generated description
Věra Hrabánková is the wife of Czech-born writer Milan Kundera and has long been known as his close partner and literary collaborator.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Věra Hrabánková
Target entity description: Věra Hrabánková is the wife of Czech-born writer Milan Kundera and has long been known as his close partner and literary collaborator.
  • A. Věra Davidová
    Věra Davidová was the daughter of Ottla Kafka, making her a niece of the writer Franz Kafka.
  • B. Milada Rádlová
    Milada Rádlová was the daughter of Emil Hácha, the third president of Czechoslovakia during the early years of World War II.
  • C. Marie Jana Körbelová
    Marie Jana Körbelová is the birth name of Madeleine Albright, the first female United States Secretary of State and a prominent American diplomat.
  • D. Dagmar Pecková
    Dagmar Pecková is a renowned Czech mezzo-soprano opera singer known for her performances on major European stages and her interpretations of both classical and contemporary repertoire.
  • E. Zora Rozsypalová
    Zora Rozsypalová was a Czech actress known for her work in theater and film during the mid-20th century.
  • 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_69c008f77ff88190b0cd50ca207295d1 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f5e8ce08190b7f5f2131bebcd4f completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04cc5f37881909f9aa8090f6c9685 completed March 22, 2026, 8:10 p.m.
NEDg Description generation batch_69c04e827bdc819086e01e7043400452 completed March 22, 2026, 8:18 p.m.
NED2 Entity disambiguation (via description) batch_69c04f088a3c81909610f1a564960e0f completed March 22, 2026, 8:20 p.m.
Created at: March 22, 2026, 3:33 p.m.