Triple

T20287890
Position Surface form Disambiguated ID Type / Status
Subject John Froines E509937 entity
Predicate givenName P17 FINISHED
Object John
John Froines was an American chemist, antiwar activist, and former member of the Chicago Seven known for his role in protests against the Vietnam War.
E1424044 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 Froines, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Froines, 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 is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
  • C. John
    John is the given name of John Eales, the renowned former Australian rugby union captain and World Cup winner.
  • D. John
    John is the given first name of the American Old West outlaw and gunfighter Johnny Ringo.
  • E. John
    John is the given name of American novelist and historical fiction writer John Jakes, best known for his sprawling family sagas set during pivotal periods of U.S. history.
  • 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 Froines, givenName, John]
Generated description
John Froines was an American chemist, antiwar activist, and former member of the Chicago Seven known for his role in protests against the Vietnam War.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John Froines was an American chemist, antiwar activist, and former member of the Chicago Seven known for his role in protests against the Vietnam War.
  • A. John
    John is the given name of John Howard Yoder, an influential American Mennonite theologian known for his work on Christian pacifism and ethics.
  • B. John
    John is the given name of the American chemist John F. Hartwig, renowned for his pioneering work in organometallic chemistry and catalysis.
  • C. John
    John Seigenthaler was an American journalist, editor, and civil rights advocate best known for his long tenure at The Tennessean and his work promoting First Amendment rights.
  • D. John
    John is the given name of John W. Cahn, a prominent American materials scientist known for his influential work in the theory of phase transformations and materials microstructure.
  • E. John
    John is the given name of John F. Clauser, an American physicist and Nobel laureate known for his pioneering experimental tests of quantum entanglement and Bell's inequalities.
  • 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_69e0b4c652388190b782cad965e5a098 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6769414488190b38e07fd1e989aba completed April 20, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0861113cbc819084930fba3b5bd5aa completed May 16, 2026, 12:20 p.m.
NEDg Description generation batch_6a0863e43ee48190bb5d384f82b62ab1 completed May 16, 2026, 12:32 p.m.
NED2 Entity disambiguation (via description) batch_6a08647647048190a5d635db1313822d completed May 16, 2026, 12:35 p.m.
Created at: April 16, 2026, 11:09 a.m.