Triple

T3686200
Position Surface form Disambiguated ID Type / Status
Subject Yvonne Zima E78230 entity
Predicate familyName P18 FINISHED
Object Zima
Zima is a surname most notably associated with a family of American actresses, including Yvonne Zima and her sisters Madeline and Vanessa.
 E379249 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: Zima | Statement: [Yvonne Zima, familyName, Zima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zima
Context triple: [Yvonne Zima, familyName, Zima]
  • A. Frunze
    Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
  • B. Prokhladny
    Prokhladny is a town in the Kabardino-Balkar Republic of Russia, known as an agricultural and transport center in the North Caucasus region.
  • C. Śnieżka
    Śnieżka is a prominent mountain peak on the border of Poland and the Czech Republic, renowned as the tallest summit in the Sudetes range and a popular hiking destination.
  • D. Ozem
    Ozem is a biblical figure mentioned in the Old Testament as one of Jesse’s sons and thus a brother of King David.
  • E. Yunaska
    Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
  • 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: Zima
Triple: [Yvonne Zima, familyName, Zima]
Generated description
Zima is a surname most notably associated with a family of American actresses, including Yvonne Zima and her sisters Madeline and Vanessa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zima
Target entity description: Zima is a surname most notably associated with a family of American actresses, including Yvonne Zima and her sisters Madeline and Vanessa.
  • A. Frunze
    Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
  • B. Prokhladny
    Prokhladny is a town in the Kabardino-Balkar Republic of Russia, known as an agricultural and transport center in the North Caucasus region.
  • C. Śnieżka
    Śnieżka is a prominent mountain peak on the border of Poland and the Czech Republic, renowned as the tallest summit in the Sudetes range and a popular hiking destination.
  • D. Ozem
    Ozem is a biblical figure mentioned in the Old Testament as one of Jesse’s sons and thus a brother of King David.
  • E. Yunaska
    Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
  • 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_69ad85e285a081908f8cbfa9e2ed9b75 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc4c676748190b074abfb9ba43b49 completed March 8, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3bd473c8190b814689f3c76cada completed March 14, 2026, 2:11 a.m.
NEDg Description generation batch_69b4c463b53c8190b3333fda95862545 completed March 14, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_69b4c4ee4db88190810a1d49d757b2b6 completed March 14, 2026, 2:16 a.m.
Created at: March 8, 2026, 3:26 p.m.