Triple

T584043
Position Surface form Disambiguated ID Type / Status
Subject Claire Bloom E15119 entity
Predicate familyName P18 FINISHED
Object Blume
Blume is the family name of acclaimed English actress Claire Bloom, known for her work in film, television, and theatre.
 E72917 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: Blume | Statement: [Claire Bloom, familyName, Blume]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blume
Context triple: [Claire Bloom, familyName, Blume]
  • A. Rosa
    Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
  • B. Sylvia
    Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Edelweiss
    "Edelweiss" is a gentle, nostalgic song from the musical *The Sound of Music*, widely recognized as one of Richard Rodgers and Oscar Hammerstein II’s most beloved compositions.
  • E. Howl
    "Howl" is a landmark 1956 poem by Allen Ginsberg that became one of the defining works of the Beat Generation, known for its raw, free-verse critique of postwar American society and its central role in an obscenity trial that expanded literary freedom.
  • 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: Blume
Triple: [Claire Bloom, familyName, Blume]
Generated description
Blume is the family name of acclaimed English actress Claire Bloom, known for her work in film, television, and theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blume
Target entity description: Blume is the family name of acclaimed English actress Claire Bloom, known for her work in film, television, and theatre.
  • A. Rosa
    Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
  • B. Sylvia
    Sylvia is a feminine given name of Latin origin meaning "from the forest" or "of the woods."
  • C. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • D. Edelweiss
    "Edelweiss" is a gentle, nostalgic song from the musical *The Sound of Music*, widely recognized as one of Richard Rodgers and Oscar Hammerstein II’s most beloved compositions.
  • E. Howl
    "Howl" is a landmark 1956 poem by Allen Ginsberg that became one of the defining works of the Beat Generation, known for its raw, free-verse critique of postwar American society and its central role in an obscenity trial that expanded literary freedom.
  • 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.