Triple

T14817307
Position Surface form Disambiguated ID Type / Status
Subject Luba Kadison E348350 entity
Predicate familyName P18 FINISHED
Object Kadison
Kadison is a surname most notably associated with Luba Kadison, a prominent actress in Yiddish theater.
E1122545 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: Kadison | Statement: [Luba Kadison, familyName, Kadison]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kadison
Context triple: [Luba Kadison, familyName, Kadison]
  • A. Knudtson
    Knudtson is a surname most notably associated with American film editor Frederic Knudtson.
  • B. Kac
    Kac is a surname most notably associated with Polish-American mathematician Mark Kac, known for his work in probability theory and mathematical physics.
  • C. Casselman
    Casselman is a small bilingual village and municipality in Eastern Ontario, Canada, known for its francophone community and location along the South Nation River.
  • D. Kempner
    Kempner is a surname most notably associated with Karen Kempner Zuckerberg, the mother of Facebook co-founder Mark Zuckerberg.
  • E. Kahn-Ackermann
    Kahn-Ackermann is a German surname most notably borne by the politician and diplomat Georg Kahn-Ackermann.
  • 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: Kadison
Triple: [Luba Kadison, familyName, Kadison]
Generated description
Kadison is a surname most notably associated with Luba Kadison, a prominent actress in Yiddish theater.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kadison
Target entity description: Kadison is a surname most notably associated with Luba Kadison, a prominent actress in Yiddish theater.
  • A. Knudtson
    Knudtson is a surname most notably associated with American film editor Frederic Knudtson.
  • B. Kac
    Kac is a surname most notably associated with Polish-American mathematician Mark Kac, known for his work in probability theory and mathematical physics.
  • C. Casselman
    Casselman is a small bilingual village and municipality in Eastern Ontario, Canada, known for its francophone community and location along the South Nation River.
  • D. Kempner
    Kempner is a surname most notably associated with Karen Kempner Zuckerberg, the mother of Facebook co-founder Mark Zuckerberg.
  • E. Kahn-Ackermann
    Kahn-Ackermann is a German surname most notably borne by the politician and diplomat Georg Kahn-Ackermann.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe2c1ec81908b3dff7a5d0e85d0 completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe3897691c819085ef89480e730723 completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe5178e8b481909c88ee7db29f037c completed May 8, 2026, 9:11 p.m.
NED2 Entity disambiguation (via description) batch_69fe5217512c8190b0cea476f4b95007 completed May 8, 2026, 9:13 p.m.
Created at: April 10, 2026, 1:50 a.m.