Triple

T11984846
Position Surface form Disambiguated ID Type / Status
Subject Willy Wonka & the Chocolate Factory E285250 entity
Predicate castMember P1668 FINISHED
Object Diana Sowle
Diana Sowle was an American actress best known for playing Charlie Bucket’s mother in the 1971 film "Willy Wonka & the Chocolate Factory."
E1028128 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: Diana Sowle | Statement: [Willy Wonka & the Chocolate Factory, castMember, Diana Sowle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diana Sowle
Context triple: [Willy Wonka & the Chocolate Factory, castMember, Diana Sowle]
  • A. Elizabeth B. Prelogar
    Elizabeth B. Prelogar is an American lawyer and legal scholar who serves as the chief advocate for the U.S. government before the Supreme Court.
  • B. Kaye V. Dowling
    Kaye V. Dowling was the wife of American film, radio, and television actor Hugh Marlowe.
  • C. Barbara M. Rolph
    Barbara M. Rolph was the woman who sponsored the U.S. Navy heavy cruiser USS San Francisco (CA-38) at its launching ceremony.
  • D. Judie G. Hoyt
    Judie G. Hoyt is a film producer best known for her work on the acclaimed crime drama "Mystic River."
  • E. Bonnie J. Dunbar
    Bonnie J. Dunbar is an American engineer and former NASA astronaut who flew on five Space Shuttle missions and later became a prominent leader in aerospace education and research.
  • 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: Diana Sowle
Triple: [Willy Wonka & the Chocolate Factory, castMember, Diana Sowle]
Generated description
Diana Sowle was an American actress best known for playing Charlie Bucket’s mother in the 1971 film "Willy Wonka & the Chocolate Factory."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Diana Sowle
Target entity description: Diana Sowle was an American actress best known for playing Charlie Bucket’s mother in the 1971 film "Willy Wonka & the Chocolate Factory."
  • A. Elizabeth B. Prelogar
    Elizabeth B. Prelogar is an American lawyer and legal scholar who serves as the chief advocate for the U.S. government before the Supreme Court.
  • B. Kaye V. Dowling
    Kaye V. Dowling was the wife of American film, radio, and television actor Hugh Marlowe.
  • C. Barbara M. Rolph
    Barbara M. Rolph was the woman who sponsored the U.S. Navy heavy cruiser USS San Francisco (CA-38) at its launching ceremony.
  • D. Judie G. Hoyt
    Judie G. Hoyt is a film producer best known for her work on the acclaimed crime drama "Mystic River."
  • E. Bonnie J. Dunbar
    Bonnie J. Dunbar is an American engineer and former NASA astronaut who flew on five Space Shuttle missions and later became a prominent leader in aerospace education and research.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903acbb9081908fe7f8360057785c completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fef515488190957a69e1cc901d65 completed May 3, 2026, 7:53 a.m.
NEDg Description generation batch_69f6ffeec1e8819090e1917fc6449ede completed May 3, 2026, 7:57 a.m.
NED2 Entity disambiguation (via description) batch_69f7017d8d308190bb54958764026325 completed May 3, 2026, 8:04 a.m.
Created at: April 8, 2026, 9:46 p.m.