Triple

T438472
Position Surface form Disambiguated ID Type / Status
Subject John Armstrong Jr. E10062 entity
Predicate givenName P17 FINISHED
Object John
John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and beyond.
E55602 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 Armstrong Jr., givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Armstrong Jr., 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 Hancock, a prominent American statesman and patriot best known for his large signature on the United States Declaration of Independence.
  • C. John
    John is the given first name of J. Edgar Hoover, the long-serving and influential first director of the United States Federal Bureau of Investigation (FBI).
  • D. 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.
  • E. John
    John is the given first name of the legendary American professional golfer Byron Nelson, one of the sport’s early great champions.
  • 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 Armstrong Jr., givenName, John]
Generated description
John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and beyond.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and beyond.
  • A. John chosen
    John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
  • B. 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.
  • C. John
    John is the given name of John Proctor, a historical figure best known as a farmer executed during the Salem witch trials and later popularized as a central character in Arthur Miller’s play "The Crucible."
  • D. 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.
  • E. 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.
  • F. None of above.

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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef283be881909444aaf257451747 completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7bffe8a488190939b1a778db4f517 completed March 4, 2026, 5:15 a.m.
NEDg Description generation batch_69a7c0bea40481908df44214da39135e completed March 4, 2026, 5:18 a.m.
NED2 Entity disambiguation (via description) batch_69a7c125de38819084897b25887dea0e completed March 4, 2026, 5:20 a.m.
Created at: Feb. 28, 2026, 1:11 p.m.