Triple

T11666197
Position Surface form Disambiguated ID Type / Status
Subject Paul Douglas E277253 entity
Predicate spouse P13 FINISHED
Object Virginia Field
Virginia Field was a British-born film and television actress active in Hollywood from the 1930s through the 1960s, known for her roles in dramas and comedies.
 E939287 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: Virginia Field | Statement: [Paul Douglas, spouse, Virginia Field]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Virginia Field
Context triple: [Paul Douglas, spouse, Virginia Field]
  • A. Virginia Fields
    Virginia Fields is known as the wife of legendary American football coach and broadcaster John Madden.
  • B. Glenwillow
    Glenwillow is a small village in northeastern Ohio that forms part of the Greater Cleveland metropolitan area.
  • C. Chelsea Field
    Chelsea Field is an American actress and former dancer known for roles in films like "The Last Boy Scout" and "Masters of the Universe," as well as for her television work.
  • D. Mary Field
    Mary Field was an American character actress known for her numerous supporting roles in Hollywood films from the 1930s through the 1950s.
  • E. Winfield
    Winfield is a small town located in Lake County, Indiana, known primarily as a residential community near the Chicago metropolitan area.
  • 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: Virginia Field
Triple: [Paul Douglas, spouse, Virginia Field]
Generated description
Virginia Field was a British-born film and television actress active in Hollywood from the 1930s through the 1960s, known for her roles in dramas and comedies.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Virginia Field
Target entity description: Virginia Field was a British-born film and television actress active in Hollywood from the 1930s through the 1960s, known for her roles in dramas and comedies.
  • A. Virginia Fields
    Virginia Fields is known as the wife of legendary American football coach and broadcaster John Madden.
  • B. Glenwillow
    Glenwillow is a small village in northeastern Ohio that forms part of the Greater Cleveland metropolitan area.
  • C. Chelsea Field
    Chelsea Field is an American actress and former dancer known for roles in films like "The Last Boy Scout" and "Masters of the Universe," as well as for her television work.
  • D. Mary Field
    Mary Field was an American character actress known for her numerous supporting roles in Hollywood films from the 1930s through the 1950s.
  • E. Winfield
    Winfield is a small town located in Lake County, Indiana, known primarily as a residential community near the Chicago metropolitan area.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13a2f1dc8190bb9ca8879ef42e14 completed April 27, 2026, 7:43 a.m.
NEDg Description generation batch_69ef3550fae881909246cd4cca047a19 completed April 27, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69ef519f95488190b4b5a167aa930133 completed April 27, 2026, 12:08 p.m.
Created at: April 8, 2026, 9:39 p.m.