Triple

T2120187
Position Surface form Disambiguated ID Type / Status
Subject Lilies of the Field E43901 entity
Predicate editedBy P1954 FINISHED
Object John McCafferty
John McCafferty is an editor and scholar known for his work on the book "Lilies of the Field."
 E265223 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: John McCafferty | Statement: [Lilies of the Field, editedBy, John McCafferty]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John McCafferty
Context triple: [Lilies of the Field, editedBy, John McCafferty]
  • A. John Killoran
    John Killoran is an actor known for his role in the National Theatre’s acclaimed stage production of "Frankenstein."
  • B. Ed McCauley
    Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
  • C. Tony Geraghty
    Tony Geraghty was a member of the popular Irish cabaret group the Miami Showband who was killed in the notorious 1975 loyalist paramilitary attack in Northern Ireland.
  • D. Michael McCusker
    Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
  • E. Francis Keally
    Francis Keally was an American architect best known for his work on major public buildings in the early 20th century, particularly in New York City.
  • 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: John McCafferty
Triple: [Lilies of the Field, editedBy, John McCafferty]
Generated description
John McCafferty is an editor and scholar known for his work on the book "Lilies of the Field."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John McCafferty
Target entity description: John McCafferty is an editor and scholar known for his work on the book "Lilies of the Field."
  • A. John Killoran
    John Killoran is an actor known for his role in the National Theatre’s acclaimed stage production of "Frankenstein."
  • B. Ed McCauley
    Ed McCauley is a Canadian academic and research leader who serves as president of the University of Calgary.
  • C. Tony Geraghty
    Tony Geraghty was a member of the popular Irish cabaret group the Miami Showband who was killed in the notorious 1975 loyalist paramilitary attack in Northern Ireland.
  • D. Michael McCusker
    Michael McCusker is an American film editor known for his work on major Hollywood productions, including the thriller "The Girl on the Train" (2016).
  • E. Francis Keally
    Francis Keally was an American architect best known for his work on major public buildings in the early 20th century, particularly in New York City.
  • 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_69a88717cfe48190b7ecdd68c824848a completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb32efb48190bcb99f30787a3a55 completed March 7, 2026, 5:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf11478c8190988a280a5088b25d completed March 9, 2026, 12:37 p.m.
NEDg Description generation batch_69aec3cf3d8881908d0e5d72f625634c completed March 9, 2026, 12:57 p.m.
NED2 Entity disambiguation (via description) batch_69aec488a4448190b2e9bf40a0fea5ee completed March 9, 2026, 1 p.m.
Created at: March 4, 2026, 7:44 p.m.