Triple

T11991641
Position Surface form Disambiguated ID Type / Status
Subject John Baldessari E285419 entity
Predicate givenName P17 FINISHED
Object John
John Baldessari was an influential American conceptual artist known for his pioneering use of found photography, text, and appropriation in contemporary art.
E958503 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 Baldessari, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Baldessari, givenName, John]
  • A. John
    John is the given name of John J. Pershing, the famed American general who led the American Expeditionary Forces in World War I.
  • B. John
    John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
  • C. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • D. John
    John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
  • E. John
    John is the given name of John Eales, the renowned former Australian rugby union captain and World Cup winner.
  • 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 Baldessari, givenName, John]
Generated description
John Baldessari was an influential American conceptual artist known for his pioneering use of found photography, text, and appropriation in contemporary art.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John Baldessari was an influential American conceptual artist known for his pioneering use of found photography, text, and appropriation in contemporary art.
  • A. John
    John is the given name of the American poet and performance artist John Giorno, a key figure in the New York avant-garde and a collaborator of Andy Warhol.
  • B. John
    John Lautner was an influential American architect known for his innovative, futuristic residential designs in Southern California.
  • C. John
    John is the given name of John Warhola, an American figure best known as the older brother of pop artist Andy Warhol and a key preserver of his legacy.
  • D. John
    John is the given name of John Ashbery, an influential American poet associated with the New York School.
  • E. John
    John Lasseter is an American animator, director, and producer best known for his pioneering work at Pixar and his role in revolutionizing computer-animated films.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903b11ac481909866b611380792e7 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f471ba7fd88190909596e6e01e8714 completed May 1, 2026, 9:26 a.m.
NEDg Description generation batch_69f47b7c5af08190ab0bff1232530a0c completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47dd51e648190bddd41766221e22d completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.