Triple

T18944657
Position Surface form Disambiguated ID Type / Status
Subject Fay Weldon E463478 entity
Predicate spouse P13 FINISHED
Object Ronald Weldon
Ronald Weldon was the husband of British novelist and feminist writer Fay Weldon.
E1350619 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: Ronald Weldon | Statement: [Fay Weldon, spouse, Ronald Weldon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ronald Weldon
Context triple: [Fay Weldon, spouse, Ronald Weldon]
  • A. William Ronald
    William Ronald was an American political figure from Virginia who served as a delegate to the Continental Congress during the Revolutionary era.
  • B. Ronald Davidson
    Ronald Davidson was an American screenwriter best known for his prolific work on action-packed film serials and B-movie adventures during the mid-20th century.
  • C. Ronald Pugh
    Ronald Pugh is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Pugh.
  • D. Ronald Williams
    Ronald Williams, better known as Ronald "Slim" Williams, is an American music executive and co-founder of the influential hip-hop label Cash Money Records.
  • E. Ronald Wolfe
    Ronald Wolfe was a British television comedy writer best known for co-creating popular sitcoms such as "The Rag Trade."
  • 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: Ronald Weldon
Triple: [Fay Weldon, spouse, Ronald Weldon]
Generated description
Ronald Weldon was the husband of British novelist and feminist writer Fay Weldon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ronald Weldon
Target entity description: Ronald Weldon was the husband of British novelist and feminist writer Fay Weldon.
  • A. William Ronald
    William Ronald was an American political figure from Virginia who served as a delegate to the Continental Congress during the Revolutionary era.
  • B. Ronald Davidson
    Ronald Davidson was an American screenwriter best known for his prolific work on action-packed film serials and B-movie adventures during the mid-20th century.
  • C. Ronald Pugh
    Ronald Pugh is a notable individual distinguished enough to be specifically recognized as a prominent bearer of the surname Pugh.
  • D. Ronald Williams
    Ronald Williams, better known as Ronald "Slim" Williams, is an American music executive and co-founder of the influential hip-hop label Cash Money Records.
  • E. Ronald Wolfe
    Ronald Wolfe was a British television comedy writer best known for co-creating popular sitcoms such as "The Rag Trade."
  • 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_69d8dcfec90481909e926be9767e5779 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d53e6e0c81908a547e21c4819bac completed April 20, 2026, 7:26 a.m.
NED1 Entity disambiguation (via context triple) batch_6a059fc93e0c81908cc4b9755036ea29 completed May 14, 2026, 10:11 a.m.
NEDg Description generation batch_6a05a1b640488190934aa468b3638841 completed May 14, 2026, 10:19 a.m.
NED2 Entity disambiguation (via description) batch_6a05a21b8a7c81909ad3f4148842e4c1 completed May 14, 2026, 10:21 a.m.
Created at: April 10, 2026, 11:59 a.m.