Triple

T11983730
Position Surface form Disambiguated ID Type / Status
Subject Billy Dee Williams E285222 entity
Predicate spouse P13 FINISHED
Object Marlene Clark
Marlene Clark is an American actress and model best known for her roles in 1970s films such as "Ganja & Hess" and "Enter the Dragon."
E958240 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: Marlene Clark | Statement: [Billy Dee Williams, spouse, Marlene Clark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marlene Clark
Context triple: [Billy Dee Williams, spouse, Marlene Clark]
  • A. Patricia Blair
    Patricia Blair was an American film and television actress best known for her roles in 1960s TV series such as "Daniel Boone" and "The Rifleman."
  • B. Janet Turnbull
    Janet Turnbull is the wife of American novelist John Irving, known for accompanying him at literary events and in public life.
  • C. Diane Smith
    Diane Smith is known as the wife of Frederick W. Smith, the founder and longtime CEO of FedEx.
  • D. Barbara Carr
    Barbara Carr is a music industry executive and longtime manager of Bruce Springsteen who co-produced his acclaimed stage production "Springsteen on Broadway."
  • E. Patricia Rice
    Patricia Rice is an American author best known for her historical and contemporary romance novels, often featuring strong heroines and elements of fantasy.
  • 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: Marlene Clark
Triple: [Billy Dee Williams, spouse, Marlene Clark]
Generated description
Marlene Clark is an American actress and model best known for her roles in 1970s films such as "Ganja & Hess" and "Enter the Dragon."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Marlene Clark
Target entity description: Marlene Clark is an American actress and model best known for her roles in 1970s films such as "Ganja & Hess" and "Enter the Dragon."
  • A. Patricia Blair
    Patricia Blair was an American film and television actress best known for her roles in 1960s TV series such as "Daniel Boone" and "The Rifleman."
  • B. Janet Turnbull
    Janet Turnbull is the wife of American novelist John Irving, known for accompanying him at literary events and in public life.
  • C. Diane Smith
    Diane Smith is known as the wife of Frederick W. Smith, the founder and longtime CEO of FedEx.
  • D. Barbara Carr
    Barbara Carr is a music industry executive and longtime manager of Bruce Springsteen who co-produced his acclaimed stage production "Springsteen on Broadway."
  • E. Patricia Rice
    Patricia Rice is an American author best known for her historical and contemporary romance novels, often featuring strong heroines and elements of fantasy.
  • 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_69d903973c848190aac871d6dfecc74b completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f472286edc8190ac72d7dd2b646c91 completed May 1, 2026, 9:28 a.m.
NEDg Description generation batch_69f47b7c5af08190ab0bff1232530a0c completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47dd51e648190bddd41766221e22d completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.