Triple

T8738085
Position Surface form Disambiguated ID Type / Status
Subject James Coburn E207434 entity
Predicate spouse P13 FINISHED
Object Paula Murad Coburn
Paula Murad Coburn was the second wife of actor James Coburn, known for her work as an actress and for managing and preserving his legacy after his death.
E755744 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: Paula Murad Coburn | Statement: [James Coburn, spouse, Paula Murad Coburn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paula Murad Coburn
Context triple: [James Coburn, spouse, Paula Murad Coburn]
  • A. Anna Kashfi
    Anna Kashfi was a British-Indian actress and the first wife of Hollywood star Marlon Brando.
  • B. Mary Barakat
    Mary Barakat is known primarily as the wife of renowned Egyptian film director Henry Barakat.
  • C. Lila Yacoub
    Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
  • D. Riza Aziz
    Riza Aziz is a Malaysian film producer and co-founder of Red Granite Pictures, known for financing high-profile Hollywood films and being embroiled in the 1MDB corruption scandal.
  • E. Farida Jalal
    Farida Jalal is a veteran Indian film and television actress known for her versatile character roles and memorable performances across Hindi cinema since the 1960s.
  • 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: Paula Murad Coburn
Triple: [James Coburn, spouse, Paula Murad Coburn]
Generated description
Paula Murad Coburn was the second wife of actor James Coburn, known for her work as an actress and for managing and preserving his legacy after his death.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Paula Murad Coburn
Target entity description: Paula Murad Coburn was the second wife of actor James Coburn, known for her work as an actress and for managing and preserving his legacy after his death.
  • A. Anna Kashfi
    Anna Kashfi was a British-Indian actress and the first wife of Hollywood star Marlon Brando.
  • B. Mary Barakat
    Mary Barakat is known primarily as the wife of renowned Egyptian film director Henry Barakat.
  • C. Lila Yacoub
    Lila Yacoub is a film producer known for her work on independent features such as Noah Baumbach’s comedy-drama "Mistress America."
  • D. Riza Aziz
    Riza Aziz is a Malaysian film producer and co-founder of Red Granite Pictures, known for financing high-profile Hollywood films and being embroiled in the 1MDB corruption scandal.
  • E. Farida Jalal
    Farida Jalal is a veteran Indian film and television actress known for her versatile character roles and memorable performances across Hindi cinema since the 1960s.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d470c8c81909ead395ef704c6ba completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42c9140081909f9c10560757c860 completed April 3, 2026, 4:32 a.m.
NEDg Description generation batch_69cf43ead588819094089bea94c27207 completed April 3, 2026, 4:36 a.m.
NED2 Entity disambiguation (via description) batch_69cf453fa3e4819082466c59649c2f35 completed April 3, 2026, 4:42 a.m.
Created at: March 30, 2026, 6:38 p.m.