Triple

T15097917
Position Surface form Disambiguated ID Type / Status
Subject John Hay Whitney E360588 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John Hay Whitney, an American businessman, diplomat, publisher, and prominent art patron.
E1138192 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 | Statement: [John Hay Whitney, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Hay Whitney, givenName, John]
  • A. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • B. John
    John Ross is a personal name shared by various notable individuals across history, including leaders, politicians, and public figures.
  • C. John
    John is the given name of John Adams, the second president of the United States and a prominent Founding Father.
  • D. John
    John is the given name of John C. Sheehan, an American organic chemist renowned for achieving the first complete laboratory synthesis of penicillin.
  • E. John
    John is the given name of John Bowen, a British novelist and playwright known for his crime and speculative fiction.
  • 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
Triple: [John Hay Whitney, givenName, John]
Generated description
John is the given name of John Hay Whitney, an American businessman, diplomat, publisher, and prominent art patron.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John Hay Whitney, an American businessman, diplomat, publisher, and prominent art patron.
  • A. John
    John is the given name of John D. Rockefeller Jr., the American philanthropist and heir to the Rockefeller family fortune.
  • B. John
    John is the given name of John J. Raskob, the American businessman and financier known for his role in the development of the Empire State Building and his leadership at General Motors and DuPont.
  • C. John
    John is the given name of John M. Olin, an American industrialist and philanthropist known for his leadership of the Olin Corporation and his influential charitable foundation.
  • D. John
    John is the given name of John D. Rockefeller III, an American philanthropist and prominent member of the Rockefeller family.
  • E. John
    John is the given name of the influential American financier and banker J. P. Morgan, a central figure in early 20th-century U.S. finance and industry.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054f00388190a5123d9f4a869b96 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feb7e47b20819084145008474f47b7 completed May 9, 2026, 4:28 a.m.
NEDg Description generation batch_69feb9abd8588190bcf43f9974429c4d completed May 9, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69feba30cc748190bc0141b205f7e91b completed May 9, 2026, 4:38 a.m.
Created at: April 10, 2026, 3:04 a.m.