Triple

T2041931
Position Surface form Disambiguated ID Type / Status
Subject Leo Genn E44763 entity
Predicate spouse P13 FINISHED
Object Margaret Genn
Margaret Genn was the wife of British actor and barrister Leo Genn.
E332749 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: Margaret Genn | Statement: [Leo Genn, spouse, Margaret Genn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Genn
Context triple: [Leo Genn, spouse, Margaret Genn]
  • A. Margaret Gibson
    Margaret Gibson was the wife of American actor Noah Beery, associated with the early Hollywood film era.
  • B. Margaret Fink
    Margaret Fink is an Australian film producer best known for her work on influential Australian New Wave films, including the acclaimed adaptation of "My Brilliant Career."
  • C. Margaret Tucker
    Margaret Tucker was an Aboriginal Australian activist and one of the country’s first female Indigenous authors, known for her pioneering work in civil rights and welfare for Aboriginal people.
  • D. Margaret Hogan
    Margaret Hogan was the wife of legendary Major League Baseball manager and team owner Connie Mack.
  • E. Margaret Haley
    Margaret Haley was an influential American educator and labor activist who championed teachers' rights and helped pioneer the modern teachers' union movement.
  • 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: Margaret Genn
Triple: [Leo Genn, spouse, Margaret Genn]
Generated description
Margaret Genn was the wife of British actor and barrister Leo Genn.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Margaret Genn
Target entity description: Margaret Genn was the wife of British actor and barrister Leo Genn.
  • A. Margaret Gibson
    Margaret Gibson was the wife of American actor Noah Beery, associated with the early Hollywood film era.
  • B. Margaret Fink
    Margaret Fink is an Australian film producer best known for her work on influential Australian New Wave films, including the acclaimed adaptation of "My Brilliant Career."
  • C. Margaret Tucker
    Margaret Tucker was an Aboriginal Australian activist and one of the country’s first female Indigenous authors, known for her pioneering work in civil rights and welfare for Aboriginal people.
  • D. Margaret Hogan
    Margaret Hogan was the wife of legendary Major League Baseball manager and team owner Connie Mack.
  • E. Margaret Haley
    Margaret Haley was an influential American educator and labor activist who championed teachers' rights and helped pioneer the modern teachers' union movement.
  • 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_69a889159ec481908f9e4472d9f480c7 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb95587348190bb5719faeaf0aa5d completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69b235511e848190897493ab54d2f198 completed March 12, 2026, 3:38 a.m.
NEDg Description generation batch_69b2365f20dc819081b8d2beccc31c19 completed March 12, 2026, 3:43 a.m.
NED2 Entity disambiguation (via description) batch_69b237397e14819093a7192d28c59ad1 completed March 12, 2026, 3:47 a.m.
Created at: March 4, 2026, 7:39 p.m.