Triple

T1933080
Position Surface form Disambiguated ID Type / Status
Subject John Galen Howard E40988 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John Galen Howard, a prominent American architect known for his influential work on the University of California, Berkeley campus.
E265386 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 Galen Howard, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Galen Howard, 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 Galen Howard, givenName, John]
Generated description
John is the given name of John Galen Howard, a prominent American architect known for his influential work on the University of California, Berkeley campus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John Galen Howard, a prominent American architect known for his influential work on the University of California, Berkeley campus.
  • A. John
    John is the given name of the prominent American architect John Russell Pope, known for designing monumental buildings in Washington, D.C.
  • B. John
    John is the given name of John Muir, the influential Scottish-American naturalist and conservationist known as the "Father of the National Parks."
  • C. John
    John is the given name of the English architect and dramatist John Vanbrugh, known for designing Blenheim Palace and Castle Howard.
  • D. John
    John is the given name of John Hancock, a prominent American statesman and patriot best known for his large signature on the United States Declaration of Independence.
  • E. John
    John is the given name of John R. Pierce, an American engineer and scientist known for his pioneering work in communications and satellite technology.
  • 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_69a8864711648190b07bed24ed76258e completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb299f3c48190a5021d320ded4405 completed March 7, 2026, 5:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebeee5a808190981c06b78d30f004 completed March 9, 2026, 12:37 p.m.
NEDg Description generation batch_69aec43352d88190a4e9ae4f315938db completed March 9, 2026, 12:59 p.m.
NED2 Entity disambiguation (via description) batch_69aec4adb21c8190a89d53588ad75438 completed March 9, 2026, 1:01 p.m.
Created at: March 4, 2026, 7:35 p.m.