Triple

T7549282
Position Surface form Disambiguated ID Type / Status
Subject Fagan E178487 entity
Predicate hasNotableBearer P458 FINISHED
Object Peter Fagan
Peter Fagan is best known as the young journalist who became engaged to Helen Keller while working as her temporary secretary in 1916.
 E689500 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: Peter Fagan | Statement: [Fagan, hasNotableBearer, Peter Fagan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Fagan
Context triple: [Fagan, hasNotableBearer, Peter Fagan]
  • A. Paul Fagan
    Paul Fagan was an American businessman best known as the owner of the San Francisco Seals baseball team in the Pacific Coast League during the 1940s.
  • B. Andrew Fagan
    Andrew Fagan is a New Zealand singer-songwriter and poet best known as the frontman of the 1980s band The Mockers and for his later solo and literary work.
  • C. Stephen McCauley
    Stephen McCauley is an American novelist known for his witty, character-driven fiction exploring contemporary relationships and urban life.
  • D. Brian Fawcett
    Brian Fawcett was the son of British explorer Percy Fawcett, known mainly for his connection to his father's legendary Amazon expeditions and disappearance.
  • E. John Heffernan
    John Heffernan is a screenwriter best known for co-writing the cult action-thriller film "Snakes on a Plane."
  • 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: Peter Fagan
Triple: [Fagan, hasNotableBearer, Peter Fagan]
Generated description
Peter Fagan is best known as the young journalist who became engaged to Helen Keller while working as her temporary secretary in 1916.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Fagan
Target entity description: Peter Fagan is best known as the young journalist who became engaged to Helen Keller while working as her temporary secretary in 1916.
  • A. Paul Fagan
    Paul Fagan was an American businessman best known as the owner of the San Francisco Seals baseball team in the Pacific Coast League during the 1940s.
  • B. Andrew Fagan
    Andrew Fagan is a New Zealand singer-songwriter and poet best known as the frontman of the 1980s band The Mockers and for his later solo and literary work.
  • C. Stephen McCauley
    Stephen McCauley is an American novelist known for his witty, character-driven fiction exploring contemporary relationships and urban life.
  • D. Brian Fawcett
    Brian Fawcett was the son of British explorer Percy Fawcett, known mainly for his connection to his father's legendary Amazon expeditions and disappearance.
  • E. John Heffernan
    John Heffernan is a screenwriter best known for co-writing the cult action-thriller film "Snakes on a Plane."
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8b35ba481908e1e5bbf329daa33 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c90098f65c8190a3130a8c1aad5e7b completed March 29, 2026, 10:36 a.m.
NEDg Description generation batch_69c9011f006c81909b11de8eb6d39153 completed March 29, 2026, 10:38 a.m.
NED2 Entity disambiguation (via description) batch_69c9018aa1cc81909c01e2770b5953a7 completed March 29, 2026, 10:40 a.m.
Created at: March 27, 2026, 3:49 p.m.