Triple

T584081
Position Surface form Disambiguated ID Type / Status
Subject Claire Bloom E15119 entity
Predicate notableRole P22 FINISHED
Object Ursula in "Limelight"
Ursula in "Limelight" is the young dancer character portrayed by Claire Bloom in Charlie Chaplin’s 1952 film about an aging comedian and a troubled ballerina.
 E72930 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: Ursula in "Limelight" | Statement: [Claire Bloom, notableRole, Ursula in "Limelight"]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ursula in "Limelight"
Context triple: [Claire Bloom, notableRole, Ursula in "Limelight"]
  • A. Dame Van Winkle
    Dame Van Winkle is the nagging, overbearing wife of the title character in Washington Irving’s short story "Rip Van Winkle."
  • B. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • C. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • 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: Ursula in "Limelight"
Triple: [Claire Bloom, notableRole, Ursula in "Limelight"]
Generated description
Ursula in "Limelight" is the young dancer character portrayed by Claire Bloom in Charlie Chaplin’s 1952 film about an aging comedian and a troubled ballerina.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ursula in "Limelight"
Target entity description: Ursula in "Limelight" is the young dancer character portrayed by Claire Bloom in Charlie Chaplin’s 1952 film about an aging comedian and a troubled ballerina.
  • A. Dame Van Winkle
    Dame Van Winkle is the nagging, overbearing wife of the title character in Washington Irving’s short story "Rip Van Winkle."
  • B. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • C. Luce
    Luce is a surname most notably associated with Henry Luce, the influential American magazine magnate and co-founder of Time Inc.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Nance
    Nance is the middle name of John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b8745c88190af9672e5fe8396c3 completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a508a1cc788190a0906bfd876e510e completed March 2, 2026, 3:48 a.m.
NEDg Description generation batch_69a50acbc7948190839d73bf48af0a67 completed March 2, 2026, 3:58 a.m.
NED2 Entity disambiguation (via description) batch_69a50b5abad08190b5abab497c61952b completed March 2, 2026, 4 a.m.
Created at: March 1, 2026, 7:33 p.m.