Triple

T1042583
Position Surface form Disambiguated ID Type / Status
Subject Matthew Boulton E22499 entity
Predicate spouse P13 FINISHED
Object Anne Boulton
Anne Boulton was the wife of prominent English industrialist and manufacturer Matthew Boulton, associated with the early Industrial Revolution in Birmingham.
E223293 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: Anne Boulton | Statement: [Matthew Boulton, spouse, Anne Boulton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne Boulton
Context triple: [Matthew Boulton, spouse, Anne Boulton]
  • A. Enid Bennett
    Enid Bennett was an Australian-born silent film actress who became a popular leading lady in early Hollywood cinema.
  • B. Frances Rudge
    Frances Rudge was the wife of influential American film and theatre director Elia Kazan.
  • C. Frances Penney
    Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
  • D. Mary Ryall
    Mary Ryall is the daughter of mathematician and educationalist Mary Everest Boole.
  • E. Clarissa Luard
    Clarissa Luard was a British literary editor and arts administrator known for her work supporting contemporary writers and for her marriage to novelist Salman Rushdie.
  • 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: Anne Boulton
Triple: [Matthew Boulton, spouse, Anne Boulton]
Generated description
Anne Boulton was the wife of prominent English industrialist and manufacturer Matthew Boulton, associated with the early Industrial Revolution in Birmingham.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Anne Boulton
Target entity description: Anne Boulton was the wife of prominent English industrialist and manufacturer Matthew Boulton, associated with the early Industrial Revolution in Birmingham.
  • A. Enid Bennett
    Enid Bennett was an Australian-born silent film actress who became a popular leading lady in early Hollywood cinema.
  • B. Sarah Barnard
    Sarah Barnard was the wife of renowned English scientist Michael Faraday, providing personal support throughout his career in 19th-century London.
  • C. Frances Rudge
    Frances Rudge was the wife of influential American film and theatre director Elia Kazan.
  • D. Frances Penney
    Frances Penney was the wife of Canadian physician and humanitarian Norman Bethune, accompanying parts of his medical and political journey in the early 20th century.
  • E. Mary Ryall
    Mary Ryall is the daughter of mathematician and educationalist Mary Everest Boole.
  • 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_69a493d91478819094cc01fb65564bc1 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b845fa8c8190a7b69629883b62e2 completed March 1, 2026, 10:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae02f0424481909c533774f0169ca7 completed March 8, 2026, 11:14 p.m.
NEDg Description generation batch_69ae059b6fbc81909ed89601d21dae28 completed March 8, 2026, 11:26 p.m.
NED2 Entity disambiguation (via description) batch_69ae0605faf08190a6f2204755595357 completed March 8, 2026, 11:28 p.m.
Created at: March 1, 2026, 7:42 p.m.