Triple

T10390888
Position Surface form Disambiguated ID Type / Status
Subject Turbo E244888 entity
Predicate producer P490 FINISHED
Object Susan Slagle Rogers
Susan Slagle Rogers is a music producer and audio professional known for her work in the recording industry.
 E913692 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: Susan Slagle Rogers | Statement: [Turbo, producer, Susan Slagle Rogers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Susan Slagle Rogers
Context triple: [Turbo, producer, Susan Slagle Rogers]
  • A. Joanne Rogers
    Joanne Rogers was an American concert pianist and television personality best known as the longtime wife and collaborator of children's television icon Fred Rogers and as a prominent advocate for his legacy.
  • B. Eileen Pardee
    Eileen Pardee is known as the former spouse of Anthony Dryden Marshall, the American theatrical producer and son of philanthropist Brooke Astor.
  • C. Mary Grace Slattery
    Mary Grace Slattery was the first wife of American playwright Arthur Miller, whom he married before achieving his major theatrical success.
  • D. Judith Ann Wilson Rogers
    Judith Ann Wilson Rogers is a prominent American judge who has served on the U.S. Court of Appeals for the District of Columbia Circuit.
  • E. Jane Loring
    Jane Loring was a film editor known for her work in early 20th-century American cinema.
  • 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: Susan Slagle Rogers
Triple: [Turbo, producer, Susan Slagle Rogers]
Generated description
Susan Slagle Rogers is a music producer and audio professional known for her work in the recording industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Susan Slagle Rogers
Target entity description: Susan Slagle Rogers is a music producer and audio professional known for her work in the recording industry.
  • A. Joanne Rogers
    Joanne Rogers was an American concert pianist and television personality best known as the longtime wife and collaborator of children's television icon Fred Rogers and as a prominent advocate for his legacy.
  • B. Eileen Pardee
    Eileen Pardee is known as the former spouse of Anthony Dryden Marshall, the American theatrical producer and son of philanthropist Brooke Astor.
  • C. Mary Grace Slattery
    Mary Grace Slattery was the first wife of American playwright Arthur Miller, whom he married before achieving his major theatrical success.
  • D. Judith Ann Wilson Rogers
    Judith Ann Wilson Rogers is a prominent American judge who has served on the U.S. Court of Appeals for the District of Columbia Circuit.
  • E. Jane Loring
    Jane Loring was a film editor known for her work in early 20th-century American cinema.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9b4f7d08190bcb16d3b4c8f22ad completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e4cbacad608190adddd91f13e4113b completed April 19, 2026, 12:33 p.m.
NEDg Description generation batch_69e4d9e87508819080932fac06fb754d completed April 19, 2026, 1:34 p.m.
NED2 Entity disambiguation (via description) batch_69e4dda28b0081909245b65faae3533b completed April 19, 2026, 1:50 p.m.
Created at: April 6, 2026, 12:06 p.m.