Triple

T2588338
Position Surface form Disambiguated ID Type / Status
Subject John Dryden Kuser E58056 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John Dryden Kuser, an American politician and member of a prominent New Jersey family in the early 20th century.
E279314 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 Dryden Kuser, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Dryden Kuser, givenName, John]
  • A. John
    John is traditionally regarded as the author of the New Testament’s Book of Revelation, a prophetic and apocalyptic text in Christian scripture.
  • B. John
    John is the given name of John Perry Barlow, the American poet, essayist, and co-founder of the Electronic Frontier Foundation known for his advocacy of digital rights.
  • C. John
    John is the given name of the renowned British mathematician John H. Conway, known for his work in group theory, number theory, and the invention of the Game of Life.
  • D. John
    John is the given name of John Nance Garner, who served as the 32nd vice president of the United States under President Franklin D. Roosevelt.
  • E. John
    John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
  • 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 Dryden Kuser, givenName, John]
Generated description
John is the given name of John Dryden Kuser, an American politician and member of a prominent New Jersey family in the early 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John Dryden Kuser, an American politician and member of a prominent New Jersey family in the early 20th century.
  • 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 American politician and diplomat John Kerry, a former U.S. Secretary of State and Democratic presidential nominee.
  • C. 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.
  • D. John
    John is the given name of John Foster Dulles, a prominent 20th-century American diplomat and U.S. Secretary of State during the Eisenhower administration.
  • E. John
    John is the given name of John F. Kennedy Jr., the American lawyer, journalist, and son of President John F. Kennedy.
  • 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd3fd1d608190a0cf0d12a9e6ce59 completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af654aab208190adbc5fb6bd500106 completed March 10, 2026, 12:26 a.m.
NEDg Description generation batch_69af67db8a048190ab9354fdff3f54b6 completed March 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69af689f7c4c8190a26270c57da71146 completed March 10, 2026, 12:41 a.m.
Created at: March 6, 2026, 9:49 p.m.